This article investigates the chaos control problem for the fractional-order chaotic systems containing unknown structure and input nonlinearities. Two types of nonlinearity in the control input are considered. In the first case, a general continuous nonlinearity input is supposed in the controller, and in the second case, the unknown dead-zone input is included. In each case, a proper switching adaptive controller is introduced to stabilize the fractional-order chaotic system in the presence of unknown parameters and uncertainties. The control methods are designed based on the boundedness property of the chaotic system's states, where, in the proposed methods the nonlinear/linear dynamic terms of the fractional-order chaotic systems are assumed to be fully unknown. The analytical results of the mentioned techniques are proved by the stability analysis theorem of fractional-order systems and the adaptive control method. In addition, as an application of the proposed methods, single input adaptive controllers are adopted for control of a class of three-dimensional nonlinear fractional-order chaotic systems. And finally, some numerical examples illustrate the correctness of the analytical results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Gutman and Wagner proposed the concept of matching energy (ME) and pointed out that the chemical applications of ME go back to the 1970s. Let G be a simple graph of order n and be the roots of its matching polynomial. The ME of G is defined to be the sum of the absolute values of . In this article, we characterize the graphs with minimal ME among all unicyclic and bicyclic graphs with a given diameter d. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>The synchronization problem for both continuous and discrete-time complex dynamical networks with time-varying delays is investigated. Using optimal partitioning method, time-varying delays are partitioned into l subintervals and generalized results are derived in terms of linear matrix inequalities (LMIs). New delay-dependent synchronization criteria in terms of LMIs are derived by constructing appropriate Lyapunov–Krasovskii functional, reciprocally convex combination technique and some inequality techniques. Numerical examples are given to illustrate the effectiveness and advantage of the proposed synchronization criteria. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article aims to introduce a projective synchronization approach based on adaptive fuzzy control for a class of perturbed uncertain multivariable nonaffine chaotic systems. The fuzzy-logic systems are employed to approximate online the uncertain functions. A Lyapunov approach is used to design the parameter adaptation laws and to demonstrate the boundedness of all signals of the closed-loop system as well as the convergence of the synchronization errors to bounded residual sets. Finally, numerical simulation results are presented to verify the feasibility and effectiveness of the proposed synchronization system based on fuzzy adaptive controller. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Based on the complex network theory, we explore an express delivery system in China, which consists of two delivery networks, namely, the air delivery network (ADN) and the ground delivery network (GDN). Systematic structural analysis indicates that both delivery networks exhibit small-world phenomenon, disassortative mixing behavior, and rich-club phenomenon. However, there are significant differences between ADN and GDN in terms of degree distribution property and community structure. On the basis of the Barabási-Albert model, we have proposed a network model incorporating the structural features of the two delivery networks to reveal their evolutionary mechanisms. Lastly, the parcel strength and the distance strength are analyzed, which, respectively, reflect the number of parcels and the long-haul delivery distance handled by a node city. The strengths are highly heterogeneous in both delivery networks and have intense correlations with topological structures. These works are beneficial for express enterprises to construct or extend their express delivery networks, and provide some useful insights on improving parcel delivery service. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Pseudorandom binary sequences play a significant role in many fields, such as spread spectrum communications, stochastic computation, and cryptography. The complexity measures of sequences and their relationship still remain an interesting open problem. In this article, we study on the eigenvalue of random sequences, deduce its theoretical expectation and variance of random sequences with length N, and establish the relationship between eigenvalue and Shannon's entropy. The results show that these two measures are consistent. Furthermore, the eigenvalue of random n-block sequences and its relation to Shannon's entropy are also been studied. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article is concerned with designing of a robust adaptive observer for a class of nonautonomous chaotic system with unknown parameters having unknown bounds. The proposed observer is established from the offered output measurement and robust against model uncertainties and external disturbances. Convergence analysis of the observation error dynamics is realized and proved by Lyapunov stabilization theory. Finally, for verification and demonstration, the proposed method is applied to the Chen as an autonomous chaotic system and the electrostatic transducer as a nonautonomous chaotic system. The numerical simulations illustrate the excellent performance of the proposed scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>We propose an improved discrete dynamical system model to reconstruct the gene regulatory network (GRN), then estimate the variable topology using discrete-time autosynchronization and predict the expression rate under the same condition. Although our method adopts a small number of sample time points to estimate the GRN, it could discern not only the role of the activator or repressor for each specific regulator, but also the regulatory ability of the regulator to the transcription rate of the target gene. Several examples are illustrated to verify that this method is feasible and effective for modeling the GRN and predicting the expression profile in the next cell cycle, the expression profile in the interval between two sample time points or the deficiency data. Additionally, this method provides a general tool for topology estimation of discrete-time dynamical networks. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article is concerned with the problem of state observer for complex large-scale systems with unknown time-varying delayed interactions. The class of large-scale interconnected systems under consideration is subjected to interval time-varying delays and nonlinear perturbations. By introducing a set of argumented Lyapunov–Krasovskii functionals and using a new bounding estimation technique, novel delay-dependent conditions for existence of state observers with guaranteed exponential stability are derived in terms of linear matrix inequalities (LMIs). In our design approach, the set of full-order Luenberger-type state observers are systematically derived via the use of an efficient LMI-based algorithm. Numerical examples are given to illustrate the effectiveness of the result. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article investigates the impact of network structure on innovation efficiency by establishing a simulation model of innovation process in the context of innovation networks. The results indicate that short path lengths between vertices are conductive to high efficiency of explorative innovations, dense clusters are conductive to high efficiency of exploitative innovations, and high small-worldness is conductive to high efficiency of the hybrid of these two innovations. Moreover, we discussed the reason of the results and give some suggestions to innovators and innovation policy makers. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article discusses a new methodology, which combines two efficient methods known as Monte Carlo (MC) and Stochastic-algebraic (SA) methods for stochastic analyses and probabilistic assessments in electric power systems. The main idea is to use the advantages of each former method to cover the blind spots of the other. This new method is more efficient and more accurate than SA method and also faster than MC method while is less dependent of the sampling process. In this article, the proposed method and two other ones are used to obtain the probability density function of different variables in a power system. Different examples are studied to show the effectiveness of the hybrid method. The results of the proposed method are compared to the ones obtained using the MC and SA methods. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Synchronization behavior of bursting neurons is investigated in a neuronal network ring impulsively coupled, in which each neuron exhibits chaotic bursting behavior. Based on the Lyapunov stability theory and impulsive control theory, sufficient conditions for synchronization of the multiple systems coupled with impulsive variables can be obtained. The neurons become synchronous via suitable impulsive strength and resetting period. Furthermore, the result is obtained that synchronization among neurons is weakened with the increasing of the reset period and the number of neurons. Finally, numerical simulations are provided to show the effectiveness of the theoretical results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article proposes a variational approach to describe the evolution of organization of complex systems from first principles, as increased efficiency of physical action. Most simply stated, physical action is the product of the energy and time necessary for motion. When complex systems are modeled as flow networks, this efficiency is defined as a decrease of action for one element to cross between two nodes, or endpoints of motion—a principle of least unit action. We find a connection with another principle, that of most total action, or a tendency for increase of the total action of a system. This increase provides more energy and time for minimization of the constraints to motion to decrease unit action, and therefore, to increase organization. Also, with the decrease of unit action in a system, its capacity for total amount of action increases. We present a model of positive feedback between action efficiency and the total amount of action in a complex system, based on a system of ordinary differential equations, which leads to an exponential growth with time of each and a power law relation between the two. We present an agreement of our model with data for core processing units of computers. This approach can help to describe, measure, manage, design, and predict future behavior of complex systems to achieve the highest rates of self-organization and robustness. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In the article, impulsive synchronization of chaotic bursting in Hindmarsh–Rose neuron systems with time delay via partial state signal is investigated. Based on impulsive control theory of dynamical systems, the sufficient conditions on feedback strength and impulsive interval are established to guarantee the synchronization. Numerical simulations show the effectiveness of the proposed scheme. The obtained results may be helpful to understand dynamical mechanism of signal transduction in real neuronal activity. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article implements the spatial Prisoner's Dilemma (PD) as an agent-based model. Many previous models have assumed that agents in a spatial PD interaction exclusively and deterministically within their von Neumann neighborhood. The model presented here introduces stochastic interactions within a subset of the von Neumann neighborhood. This implementation allows a direct comparison of the effect of stochastic interactions relative to deterministic interactions on the level of cooperation that emerges in the system. The results show that when holding the total number of interactions agents participate in each round constant, allowing agents to interact stochastically increases cooperation in the system relative to deterministic interactions. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article is concerned with the stabilization problem for nonlinear networked control systems which are represented by polynomial fuzzy models. Two communication features including signal transmission delays and data missing are taken into account in a network environment. To solve the network-induced communication problems, a novel sampled-data fuzzy controller is designed to guarantee that the closed-loop system is asymptotically stable. The stability and stabilization conditions are presented in terms of sum of squares (SOS), which can be numerically solved via SOSTOOLS. Finally, a simulation example is provided to demonstrate the feasibility of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, a brief stability analysis of equilibrium points in nonlinear fractional order dynamical systems is given. Then, based on the first integral concept, a definition of planar Hamiltonian systems with fractional order introduced. Some interesting properties of these fractional Hamiltonian systems are also presented. Finally, we illustrate two examples to see the differences between fractional Hamiltonian systems with their classical order counterparts. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article proposes a novel adaptive sliding mode control (SMC) scheme to realize the problem of robust tracking and model following for a class of uncertain time-delay systems with input nonlinearity. It is shown that the proposed robust tracking controller guarantees the stability of overall closed-loop system and achieves zero-tracking error in the presence of input nonlinearity, time-delays, time-varying parameter uncertainties and external disturbances. The selection of sliding surface and the existence of sliding mode are two important issues, which have been addressed. This scheme assures robustness against input nonlinearity, time-delays, parameter uncertainties, and external disturbances. Moreover, the knowledge of the upper bound of uncertainties is not required and chattering phenomenon is eliminated. Both theoretical analysis and illustrative examples demonstrate the validity of the proposed scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>The goal of this article is to build an abstract mathematical theory rather than a computational one of the process of transmission of ideology. The basis of much of the argument is Patten's Environment Theory that characterizes a system with its double environment (input or stimulus and output or response) and the existing interactions among them. Ideological processes are semiotic processes, and if in Patten's theory, the two environments are physical, in this theory ideological processes are physical and semiotic, as are stimulus and response. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Chaos synchronization is a procedure where one chaotic oscillator is forced to adjust the properties of another chaotic oscillator for all future states. This research paper studies and investigates the global chaos synchronization problem of two identical chaotic systems and two non-identical chaotic systems using the linear active control technique. Based on the Lyapunov stability theory and using the linear active control technique, the stabilizing controllers are designed for asymptotically global stability of the closed-loop system for both identical and non-identical synchronization. Numerical simulations and graphs are imparted to justify the efficiency and effectiveness of the proposed scheme. All simulations have been done by using mathematica 9. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Josephson junction oscillators can generate chaotic signals with a wide frequency spectrum. An improved scheme of Lyapunov functions is proposed to control chaotic resonators of this type and forces them to converge to an arbitrary selected target signal. A changeable gain coefficient is introduced into the Lyapunov function, and the controllers are designed analytically. The controllers operate automatically when the output series are deviated from the target orbit synchronously. A resistive-capacitive-inductive-shunted Josephson junction in chaotic parameter region is investigated in our studies, and power consumption is estimated from the dimensionless model. It is found that the power consumption of controller is dependent on the amplitude and/or angular frequency of the external target signal to be tracked. For example, larger power costs are observed when the target signal is in larger amplitude and/or angular frequency. The numerical results are consistent with the analytical discussion. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>We examine the transmission of entities from the peripheries of scale-free networks toward their centers when the nodes of the network have finite processing capabilities. We look at varying network utilization, U and find that clogging of the network sets in after a threshold value has been exceeded, and that the congestion sets in at the downstream nodes (those nearer to the collector) having large numbers of upstream neighbors. Investigation of the question of the degree of correlation of several characteristics of scale-free networks (such as the average path length to the collector <l_{(min)}> and the average clustering coefficient
) with the dynamics of centripetal flow in them reveals a negative answer: any correlation is indirect and will manifest in the number of producer nodes (which dictate the effective heaviness of the flow) and the interconnectedness of the feeder nodes, those nodes which are immediate neighbors of the collector node. An examination of reinforcement strategies shows dramatic improvements in both the finishing rate,
and the average total transmission time,
when the more centrally-placed nodes are reinforced first, showing that the entities spend a large amount of their lifetime waiting in line at those nodes (which constitute the bottlenecks in the network) compared to the nodes in the periphery. Our results reinforce the importance of a network's hubs and their immediate environs, and suggest strategies for prioritizing elements of a network for optimization. © 2014 Wiley Periodicals, Inc. Complexity, 2014

In this article, the dynamical behaviors of two classes of chaotic systems are considered based on generalized Lyapunov function theorem with integral inequalities. Explicit estimations of the ultimate bounds are derived. The results presented in this article contain the existing results as special cases. Computer simulation results show that the proposed method is effective. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article considers the composite nonlinear feedback control method for robust tracker and disturbance attenuator design of uncertain systems with time delays. The proposed robust tracker improves the transient performance and steady state accuracy simultaneously. The asymptotic robust tracking conditions are provided in the form of linear matrix inequalities and the resultant conditions yield the controller gains. Moreover, to improve the reference tracking performance, a new nonlinear function for the composite feedback control law is offered. Simulation results are presented to verify the theoretical results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article deals with optimal placement of Distributed Generation (DG) sources and recloser in simultaneous mode and develops an improved harmony search (iHS) algorithm to solve it. For this, two important control parameters have been adjusted to reach better solution from simple HS algorithm to obtain better solution from simple HS algorithm. The proposed multiobjective function consists of two parts; first is improving reliability indices and second is minimizing power loss. The reliability indices have been selected based on satisfactory requirements of costumer and electric company as well as response to transient and permanent faults. Then, four reliability indices has been used in objective function; that is, system average interruption duration index (SAIDI), cost of energy not supplied, momentary average interruption frequency index, and system average interruption frequency index (SAIFI). Simulation has been performed on a practical distribution network in North West of Iran. Three scenarios have been introduced; that is, scenario (i) First, placement of DGs, and then recloser, scenario (ii) First, placement of recloser, and then DG, and scenario (iii) simultaneous placement of DG and recloser. Also, three cases are defined based on the number of used DG and recloser. Results of the proposed algorithm have been compared with related values of particle swarm optimization and simple HS algorithms. The core contribution of the presented study is introducing several novel indices to analyze and discuss the obtained results from simulation. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Based on a market consisting of one monopoly and several customers who are embedded in an economic network, we study how the different perception levels about the network structure affect the two kinds of participants' welfares, and then provide some good strategies for the monopoly to mine the information of the network structure. The above question is the embodiment of the “complex structure and its corresponding functions” question often mentioned in the field of complexity science. We apply a two-stage game to solve for the optimal pricing and consumption at different perception levels of the monopoly and further utilize simulation analysis to explore the influence patterns. We also discuss how this theoretic model can be applied to a real world problem by introducing the statistical exponential random graph model and its estimation method. Further, the main findings have specific policy implications on uncovering network information and demonstrate that it is possible for the policy-maker to design some win–win mechanisms for uplifting both the monopoly's profit and the whole customers' welfare at the same time. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, a synchronization problem for complex dynamical networks with additive time-varying coupling delays via non-fragile control is investigated. A new class of Lyapunov–Krasovskii functional with triple integral terms is constructed and using reciprocally convex approach, some new delay-dependent synchronization criteria are derived in terms of linear matrix inequalities (LMIs). When applying Jensen's inequality to partition double integral terms in the derivation of LMI conditions, a new kind of linear combination of positive functions weighted by the inverses of squared convex parameters appears. To handle such a combination, an effective method is introduced by extending the lower bound lemma. Then, a sufficient condition for designing the non-fragile synchronization controller is introduced. Finally, a numerical example is given to show the advantages of the proposed techniques. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>A scalable model of biological evolution is presented which includes energy cost for building new elements and multiple paths for obtaining new functions. The model allows a population with a continual increase of complexity, but as time passes, detrimental mutations accumulate. This model shows the crucial importance of accounting for the energy cost of new structures in models of biological evolution. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In a genome, genes (coding constituents) are interrupted by intergenic regions (noncoding constituents). This study provides a general picture of the large-scale self-organization of coding, noncoding, and total constituent lengths in genomes. Ten model genomes were examined and strong correlations between the number of genomic constituents and the constituent lengths were observed. The analysis was carried out by adopting a linguistic distribution model and a structural analogy between linguistic and genomic constructs. The proposed linguistic-based statistical analysis may provide a fundamental basis for both understanding the linear structural formation of genomic constituents and developing insightful strategies to figure out the function of genic and intergenic regions in genomic sequences. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Why do mouse corneal epithelial cells display spiraling patterns? We want to provide an explanation for this curious phenomenon by applying an idealized problem solving process. Specifically, we applied complementary line-fitting methods to measure transgenic epithelial reporter expression arrangements displayed on three mature, live enucleated globes to clarify the problem. Two prominent logarithmic curves were discovered, one of which displayed the *ϕ* ratio, an indicator of an optimal configuration in phyllotactic systems. We then utilized two different computational approaches to expose our current understanding of the behavior. In one procedure, which involved an isotropic mechanics-based finite element method, we successfully produced logarithmic spiral curves of maximum shear strain based pathlines but computed dimensions displayed pitch angles of 35° (*ϕ* spiral is ∼17°), which was altered when we fitted the model with published measurements of coarse collagen orientations. We then used model-based reasoning in context of Peircean abduction to select a working hypothesis. Our work serves as a concise example of applying a scientific habit of mind and illustrates nuances of executing a common method to doing integrative science. © 2014 Wiley Periodicals, Inc. Complexity, 2014

The problem of scheduling independent tasks with a common deadline for a multicore processor is investigated. The speed of cores can be varied (from a finite set of core speeds) using software controlled Dynamic Voltage Scaling. The energy consumption is to be minimized. This problem was called the Energy Efficient Task Scheduling Problem (EETSP) in a previous work in which a Monte Carlo algorithm was proposed for solving it. This work investigates the complexity of the EETSP problem. The EETSP problem is proved to be NP-Complete. Under the assumption of , the EETSP problem is also proved to be inapproximable. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article proposed a new hybrid algorithm for solving power flow tracing (PFT) through the comparison by other techniques. This proposed hybrid strategy in detail discuses over the achieved results. Both methods use the active and reactive power balance equations at each bus to solve the tracing problem, where the first method considers the proportional sharing assumption and the second one considers the circuit laws to find the relationship between power inflows and outflows through each line, generator, and load connected to each bus of the network. Both algorithms are able to handle loop flow and loss issues in tracing the problem. A mathematical formulation is also introduced to find the share of each unit in provision of each load. These algorithms are employed to find the producer and consumer's shares on the cost of transmission for each line in different case studies. As the results of these studies show, both algorithms can effectively solve the PFT problem. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, the problem of reliable gain-scheduled *H _{∞}* performance optimization and controller design for a class of discrete-time networked control system (NCS) is discussed. The main aim of this work is to design a gain-scheduled controller, which consists of not only the constant parameters but also the time-varying parameter such that NCS is asymptotically stable. In particular, the proposed gain-scheduled controller is not only based on fixed gains but also the measured time-varying parameter. Further, the result is extended to obtain a robust reliable gain-scheduled

A honeybee mating optimization technique is used to tune the power system stabilizer (PSS) parameters and find optimal location of PSSs in this article. The PSS parameters and placement are computed to assure maximum damping performance under different operating conditions. One of the main advantages of the proposed approach is its robustness to the initial parameter settings. The effectiveness of the proposed method is demonstrated on two case studies as; 10-machine 39-buses New England (NE) power system in comparison with Tabu Search (TS) and 16 machines and 68 buses-modified reduced order model of the NE New York interconnected system by genetic algorithm through some performance indices under different operating condition. The proposed method of tuning the PSS is an attractive alternative to conventional fixed gain stabilizer design as it retains the simplicity of the conventional PSS and at the same time guarantees a robust acceptable performance over a wide range of operating and system condition. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article describes a nutrient-phytoplankton-zooplankton system with nutrient recycling in the presence of toxicity. We have studied the dynamical behavior of the system with delayed nutrient recycling in the first part of the article. Uniform persistent of the system is examined. In the second part of the article, we have incorporated diffusion of the plankton population to the system and dynamical behavior of the system is analyzed with instantaneous nutrient recycling. The condition of the diffusion driven instability is obtained. The conditions for the occurrence of Hopf and Turing bifurcation critical line in a spatial domain are derived. Variation of the system with small periodicity of diffusive coefficient has been studied. Stability condition of the plankton system subject to the periodic diffusion coefficient of the zooplankton is derived. It is observed that nutrient-phytoplankton-zooplankton interactions are very complex and situation specific. Moreover, we have obtained different exciting results, ranging from stable situation to cyclic oscillatory behavior may occur under different favorable conditions, which may give some insights for predictive management. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>We study self-similarity in one-dimensional probabilistic cellular automata (PCA) by applying a real-space renormalization technique to PCA with increasingly large updating neighborhoods. By studying the flow about the critical point of the renormalization, we may produce estimates of the spatial scaling properties of critical PCA. We find that agreement between our estimates and experimental values are improved by resolving correlations between larger blocks of spins, although this is not sufficient to converge to experimental values. However, applying the technique to PCA with larger neighborhoods, and, therefore, more renormalization parameters, results in further improvement. Our most refined estimate produces a spatial scaling exponent, found at the critical point of the five-neighbor PCA, of ν = 1.056 which should be compared to the experimental value of ν = 1.097. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Islanding is an important concern for grid-connected distributed resources due to personnel and equipment safety issues. Several techniques based on passive and active detection schemes have been proposed previously. Although passive schemes have a large nondetection zone (NDZ), concerns have been raised about active methods because of their degrading effect on power quality. Reliably detecting this condition is regarded by many as an ongoing challenge because existing methods are not entirely satisfactory. This article proposes a new integrated histogram analysis method using a neuro-fuzzy approach for islanding detection in grid-connected wind turbines. The main objective of the proposed approach is to reduce the NDZ to as close as possible to zero and to maintain the output power quality unchanged. In addition, this technique can also overcome the problem of setting detection thresholds which is inherent in existing techniques. The method proposed in this study has a small NDZ and is capable of detecting islanding accurately within the minimum standard time. Moreover, for those regions which require better visualization, the proposed approach can serve as an efficient aid for better detecting grid-power disconnection. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article considers the problem of consensus for discrete-time networks of multiagent with time-varying delays and quantization. It is assumed that the logarithmic quantizer is utilized between the information flow through the sensor of each agent, and its quantization error is included in the proposed method. By constructing a suitable Lyapunov-Krasovskii functional and utilizing matrix theory, a new consensus criterion for the concerned systems is established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Based on the consensus criterion, a designing method of consensus protocol is introduced. One numerical example is given to illustrate the effectiveness of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>The recent discovery of memristive neurodynamic systems holds great promise for realizing large-scale nanoionic circuits. Development of pattern memory analysis for memristive neurodynamic systems poses several challenges. In this article, it shows that an n-dimensional memristive neural networks with time-varying delays can have 2^{n} locally exponentially stable equilibria in the saturation region. In addition, local exponential stability of delayed memristive neural networks in any designated region is also characterized, which allows the locally exponentially stable equilibria to locate in the designated region. All of these criteria are very easy to be verified. Finally, the effectiveness of the results are illustrated by two numerical examples. © 2014 Wiley Periodicals, Inc. Complexity, 2014

This article deals with the problem of robust stochastic asymptotic stability for a class of uncertain stochastic neural networks with distributed delay and multiple time-varying delays. It is noted that the reciprocally convex approach has been intensively used in stability analysis for time-delay systems in the past few years. We will extend the approach from deterministic time-delay systems to stochastic time-delay systems. And based on the new technique dealing with matrix cross-product and multiple-interval-dependent Lyapunov–Krasovskii functional, some novel delay-dependent stability criteria with less conservatism and less decision variables for the addressed system are derived in terms of linear matrix inequalities. At last, several numerical examples are given to show the effectiveness of the results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article is concerned with the problem of finite-time synchronization control for a class of discrete-time nonlinear chaotic systems under unreliable communication links. Our aim is to design a delayed feedback controller such that the resulting synchronization error system is stochastically finite-time bounded with a guaranteed performance level over a finite time interval. Some sufficient conditions for the solvability of the above problem are established. A delayed feedback control scheme involving constrained information about the past state is presented. Finally, the Fold chaotic system is used to demonstrate the effectiveness of our proposed approach. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article addresses a new modified honey bee mating optimization namely multiobjective honey bee mating optimization (MOIHBMO) based fuzzy multiobjective methodology for optimal locating and parameter setting of unified power flow controller (UPFC) in a power system for a long-term period. One of the profits obtained by UPFC placement in a transmission network is the reduction in total generation cost due to its ability to change the power flow pattern in the network. Considering this potential, UPFC can be also used to remove or at least mitigate the congestion in transmission networks. The other issue in a power system is voltage violation which could even render the optimal power flow problem infeasible to be solved. Voltage violation could be also mitigated by proper application of UPFC in a transmission system. These objectives are considered simultaneously in a unified objective function for the proposed optimization algorithm. At first, these objectives are fuzzified and designed to be comparable against each other and then they are integrated and introduced to a MOIHBMO method to find the solution which maximizes the value of integrated objective function in a 3-year planning horizon, considering the load growth. A power injection model is adopted for UPFC. Unlike, the most previous works in this field the parameters of UPFC are set for each load level to avoid inconvenient rejection of more optimal solutions. IEEE reliability test system is used as an illustrative example to show the effectiveness of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article focuses on the problem of exponential synchronization for fractional-order chaotic systems via a nonfragile controller. A criterion for α-exponential stability of an error system is obtained using the drive-response synchronization concept together with the Lyapunov stability theory and linear matrix inequalities approach. The uncertainty in system is considered with polytopic form together with structured form. The sufficient conditions are derived for two kinds of structured uncertainty, namely, (1) norm bounded one and (2) linear fractional transformation one. Finally, numerical examples are presented by taking the fractional-order chaotic Lorenz system and fractional-order chaotic Newton–Leipnik system to illustrate the applicability of the obtained theory. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, a new methodology based on fuzzy proportional-integral-derivative (PID) controller is proposed to damp low frequency oscillation in multimachine power system where the parameters of proposed controller are optimized offline automatically by hybrid genetic algorithm (GA) and particle swarm optimization (PSO) techniques. This newly proposed method is more efficient because it cope with oscillations and different operating points. In this strategy, the controller is tuned online from the knowledge base and fuzzy interference. In the proposed method, for achieving the desired level of robust performance exact tuning of rule base and membership functions (MF) are very important. The motivation for using the GA and PSO as a hybrid method are to reduce fuzzy effort and take large parametric uncertainties in to account. This newly developed control strategy mixed the advantage of GA and PSO techniques to optimally tune the rule base and MF parameters of fuzzy controller that leads to a flexible controller with simple structure while is easy to implement. The proposed method is tested on three machine nine buses and 16 machine power systems with different operating conditions in present of disturbance and nonlinearity. The effectiveness of proposed controller is compared with robust PSS that tune using PSO and the fuzzy controller which is optimized rule base by GA through figure of demerit and integral of the time multiplied absolute value of the error performance indices. The results evaluation shows that the proposed method achieves good robust performance for a wide range of load change in the presents of disturbance and system nonlinearities and is superior to the other controllers. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Smart grid is referred to a modernized power grid which can mitigate fault detection and allow self-healing of the system without the intervention of operators. This article proposes an innovative analytical formulation using Markov method to evaluate electric power distribution system reliability in smart grids, which incorporates the impact of smart monitoring on the overall system reliability. An accurate reliability model of the main network components and the communication infrastructure have been also considered in the methodology. The proposed approach was applied to a well-known test bed (Roy Billinton Test System) and various reliability case studies with monitoring provision and monitoring deficiency are analyzed. This article involves the developing possibilities of communication technologies and next-generation control systems of the entire smart network based on the real-time monitoring and modern control system to achieve a reliable, economical, safe, and high efficiency of electricity. The implementations indicate that using an appropriate set of the smart grid monitoring devices for power system components can virtually influence all the reliability indices although the amount of improvement varies between techniques. The proposed approach determined that smart monitoring for which components of the electric power distribution systems are tailored and deduce to major economical benefits. The described approach also reveals which reliability indices drastically influenced using monitoring. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, cluster synchronization problem for Lur'e type Takagi–Sugeno (T–S) fuzzy complex networks with probabilistic time-varying delays is considered. Pinning control strategy is proposed. The probability distribution of the time-varying delay is considered. In terms of the probability distribution of the delays, a new type of system model with probability-distribution-dependent parameter matrices is proposed. Moreover, probabilistic delay is assumed to satisfy certain probability distribution and the probability of the delay takes values in some intervals. By constructing a suitable Lyapunov–Krasovskii functional involving triple integral terms and using Kronecker product with convex combination technique, some sufficient conditions are derived to ensure the cluster synchronization of designed networks such that the linear feedback controller can be used to every cluster. The problem of controller design is converted into solving a series of linear matrix inequalities. The effectiveness of our results is verified through numerical examples and simulations. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, the problem of robust reliable sampled-data control for a class of uncertain nonlinear stochastic system with random delay control input against actuator failures has been studied. In the considered system, the parameter uncertainty satisfies the norm bounded condition and the involved time delay in control input are assumed to be randomly time-varying which is modeled by introducing Bernoulli distributed sequences. By constructing a novel Lyapunov–Krasovskii functional involving with the lower and upper bounds of the delay, a new set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) for ensuring the robust asymptotic stability of the uncertain nonlinear stochastic system with random delay and disturbance attenuation level about its equilibrium point for all possible actuator failures. In particular, Schur complement together with Jenson's integral inequality is utilized to substantially simplify the derivation in the main results. The derived analytic results are applied to design robust reliable sampled-data controller for hanging crane structure model and simulation results are provided to demonstrate the effectiveness of the proposed control law. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Design of a novel global sliding mode control law for the stabilization of uncertain nonlinear systems is presented in this article. A sufficient condition is derived using the Lyapunov theorem and linear matrix inequality to guarantee the asymptotical stability of the states and to improve the stability of the system. Under the uncertainty and nonlinearity effects, the reaching phase is eliminated and the chattering is reduced effectively and then, the robustness and performance of the system are improved. Lastly, the proposed method is applied on Genesio's chaotic system and the simulation results demonstrate the effectiveness of this technique. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>The mine ventilation system is most important and technical measure for ensuring safety production in mines. The structural complexity of a mine ventilation network can directly affect the safety and reliability of the underground mining system. Quantitatively justifying the degree of complexity can contribute to providing a deeper understanding of the essential characteristics of a network. However, so far, there is no such a model which is able to simply, practically, reasonably, and quantitatively determine or compare the structural complexity of different ventilation networks. In this article, by analyzing some typical parameters of a mine ventilation network, we conclude that there is a linear functional relationship among five key parameters (number of ventilation network branches, number of nodes, number of independent circuits, number of independent paths, and number of diagonal branches). Correlation analyses for the main parameters of ventilation networks are conducted based on SPSS. Based on these findings, a new evaluation model for the structural complexity of ventilation network (which is represented by C) has been proposed. By combining SPSS classification analyses results with the characteristics of mine ventilation networks, standards for the complexity classification of mine ventilation systems are put forward. Using the developed model, we carried out *analyses and comparisons for the structural complexity of ventilation networks for typical mines*. Case demonstrations show that the classification results correspond to the actual situations. © 2014 Wiley Periodicals, Inc. Complexity, 2014

Dehmer and Mowshowitz introduced a class of generalized graph entropies using known information-theoretic measures. These measures rely on assigning a probability distribution to a graph. In this article, we prove some extremal properties of such generalized graph entropies by using the graph energy and the spectral moments. Moreover, we study the relationships between the generalized graph entropies and compute the values of the generalized graph entropies for special graph classes. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article calls attention to flaws in the scientific enterprise, providing a case study of the lack of professionalism in published journal articles in a particular area of research, namely, network complexity. By offering details of a special case of poor scholarship, which is very likely indicative of a broader problem, the authors hope to stimulate editors and referees to greater vigilance, and to strengthen authors' resolve to take their professional responsibilities more seriously. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article proposes a new integrated diagnostic system for islanding detection by means of a neuro-fuzzy approach. Islanding detection and prevention is a mandatory requirement for grid-connected distributed generation (DG) systems. Several methods based on passive and active detection scheme have been proposed. Although passive schemes have a large non-detection zone (NDZ), concern has been raised on active method due to its degrading power-quality effect. Reliably detecting this condition is regarded by many as an ongoing challenge as existing methods are not entirely satisfactory. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. In addition, this technique can also overcome the problem of setting the detection thresholds inherent in the existing techniques. In this study, we propose to use a hybrid intelligent system called ANFIS (the adaptive neuro-fuzzy inference system) for islanding detection. This approach utilizes rate of change of frequency (ROCOF) at the target DG location and used as the input sets for a neuro-fuzzy inference system for intelligent islanding detection. This approach utilizes the ANFIS as a machine learning technology and fuzzy clustering for processing and analyzing the large data sets provided from network simulations using MATLAB software. To validate the feasibility of this approach, the method has been validated through several conditions and different loading, switching operation, and network conditions. The proposed algorithm is compared with the widely used ROCOF relays and found working effectively in the situations where ROCOF fails. Simulation studies showed that the ANFIS-based algorithm detects islanding situation accurate than other islanding detection algorithms. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Different from the short-term risk measure for traditional financial assets (stocks, bonds, etc.), the key to illiquid inventory portfolio traded in the over-the-counter markets is to estimate the long-term extreme price risk with time varying volatility. In this article, a new long-term extreme price risk (value at risk and conditional value at risk) measure method for inventory portfolio and an application to dynamic impawn rate interval are proposed. To realize this, we first establish AutoRegressive Moving Average-Exponential Generalized Autoregressive Conditional Heteroskedasticity-Extreme Value Theory model and multivariatet-Copula to depict the autocorrelation, fat tails, and volatility clustering of returns of inventories and the nonlinear dependence structure of inventories. Furthermore, we obtain the long-term extreme price risk with time varying volatility via Monte Carlo simulation instead of square-root-of time rule. The results show that, first, benefits from risk diversification is significant; second, long-term extreme price risk measure of inventory portfolio via Monte Carlo method outperforms the square-root-of time rule; the last is that the dynamic rate interval based on the long-term price risk is superior to the crude rules of thumb in terms of reducing efficiency loss and improving risk coverage. In summary, this article provides a new quantitative framework for managing the risk of portfolio in inventory financing practice for banks constrained by risk limitation. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article discusses the meaning and scope of biological hypercomputation (BH) that is to be considered as new research problem within the sciences of complexity. The framework here is computational, setting out that life is not a standard Turing Machine. Living systems, we claim, hypercompute, and we aim at understanding life not by what it is, but rather by what it does. The distinction is made between classical and nonclassical hypercomputation. We argue that living processes are nonclassical hypercomputation. BH implies then new computational models. Finally, we sketch out the possibilities, stances, and reach of BH. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Often relegated to the methods section of genetic research articles, the term “degeneracy” is regularly misunderstood and its theoretical significance widely understated. Degeneracy describes the ability of different structures to be conditionally interchangeable in their contribution to system functions. Frequently mislabeled redundancy, degeneracy refers to structural variation whereas redundancy refers to structural duplication. Sources of degeneracy include, but are not limited to, (1) duplicate structures that differentiate yet remain isofunctional, (2) unrelated isofunctional structures that are dispersed endogenously or exogenously, (3) variable arrangements of interacting structures that achieve the same output through multiple pathways, and (4) parcellation of a structure into subunits that can still variably perform the same initial function. The ability to perform the same function by drawing upon an array of dissimilar structures contributes advantageously to the integrity of a system. Drawing attention to the heterogeneous construction of living systems by highlighting the concept of degeneracy valuably enhances the ways scientists think about self-organization, robustness, and complexity. Labels in science, however, can sometimes be misleading. In scientific nomenclature, the word “degeneracy” has calamitous proximity to the word “degeneration” used by pathologists and the shunned theory of degeneration once promoted by eugenicists. This article disentangles the concept of degeneracy from its close etymological siblings and offers a brief overview of the historical and contemporary understandings of degeneracy in science. Distinguishing the importance of degeneracy will hopefully allow systems theorists to more strategically operationally conceptualize the distributed intersecting networks that comprise complex living systems. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article deals with the fractional-order modeling of a complex four-dimensional energy supply-demand system (FOESDS). First, the fractional calculus techniques are adopted to describe the dynamics of the energy supply-demand system. Then the complex behavior of the proposed fractional-order FOESDS is studied using numerical simulations. It is shown that the FOESDS can exhibit stable, chaotic, and unstable states. When it exhibits chaos, the FOESDS's strange attractors are plotted to validate the chaotic behavior of the system. Moreover, we calculate the maximal Lyapunov exponents of the system to confirm the existence of chaos. Accordingly, to stabilize the system, a finite-time active fractional-order controller is proposed. The effects of model uncertainties and external disturbances are also taken into account. An estimation of the stabilization time is given. Based on the latest version of the fractional Lyapunov stability theory, the finite-time stability and robustness of the proposed method are proved. Finally, two illustrative examples are provided to illustrate the usefulness and applicability of the proposed control scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article introduces a special issue of Complexity dedicated to the increasingly important element of complexity science that engages with social policy. We introduce and frame an emerging research agenda that seeks to enhance social policy by working at the interface between the social sciences and the physical sciences (including mathematics and computer science), and term this research area the “social science interface” by analogy with research at the life sciences interface. We locate and exemplify the contribution of complexity science at this new interface before summarizing the contributions collected in this special issue and identifying some common themes that run through them. © 2014 Wiley Periodicals, Inc. Complexity 19: 1–4, 2014

]]>This study suggests that cross-fertilization between complexity and social science could provide a new rationale for policy. We look at the weakness of conventional policy thinking and excessive faith in incentives and the underestimation of social interaction on individual choices. Recent examples of experimental and computational research on social interaction indicate the importance of understanding preexisting social norms and network structures for targeting appropriately contextualized policies. This would allow us to conceive policy not as something that takes place “off-line” outside systems but as a constitutive process interacting with self-organized system behavior. This article aims to pave the way for a complexity-friendly policy that allows us to understand and manage more than predict and control top-down. © 2014 Wiley Periodicals, Inc. Complexity 19: 5–13, 2014

]]>Innovation and entrepreneurship are the most important catalysts of dynamism in market economies. While it is known that entrepreneurial activities are locally embedded, mutual effects of entrepreneurs and their local regional environment have not been adequately addressed in the existing literature. In this article, we use agent-based simulation experiments to investigate the role of entrepreneurship in the emergence of regional industrial clusters. We present fundamental extensions to the Simulating Knowledge Dynamics in Innovation Networks model (Ahrweiler et al., Industry and Labor Dynamics: The Agent-based Computational Economics Approach; World Scientific: Singapore, 2004; pp 284–96) by using a multilevel modeling approach. We analyze the effects of changing entrepreneurial character of regions on the development industrial clusters in two simultaneously simulated regions. We find that an increase in the entrepreneurship of one region has a negative effect on the other region due to competition for factors of production and innovative outputs. The major policy implication of this finding is the limitation it posits on regional innovation and development policies that aspire to support clusters in similar areas of industrial specialization. © 2014 Wiley Periodicals, Inc. Complexity 19: 14–29, 2014

]]>Infrastructure, which is used to extract, transport, store, and transform resources into products or services to meet our utility needs faces numerous challenges caused by the agency of the various actors in the system. To understand these challenges, we propose it is necessary to move beyond considering each utility system as a distinct silo. In this paper, a conversion points approach is developed to characterize multiutility systems at any scale and for any specific or theoretical location. The story is told of the development of a conversion points approach and its application is examined using an agent-based model. Transport, energy, water, waste, and telecommunications systems are governed and run independently but in practice are highly interdependent. A way to represent all utility systems in an integrated way is described and the benefits of this representation are applied to UK household consumers. © 2014 Wiley Periodicals, Inc. Complexity 19: 30–43, 2014

]]>To model agent relationships in agent-based models, it is often necessary to incorporate a social network whose topology is commonly assumed to be “small-world.” This is potentially problematic, as the classification is broad and covers a wide-range of network statistics. Furthermore, real networks are often dynamic, in that edges and nodes can appear or disappear, and spatial, in that connections are influenced by an agent's position within a particular social space. These properties are difficult to achieve in current network formation tools. We have, therefore, developed a novel social network formation model, that creates and dynamically adjusts small-world networks using local spatial interactions, while maintaining tunable global network statistics from across the broad space of possible small-world networks. It is, therefore, a useful tool for multiagent simulations and diffusion processes, particularly those in which agents and edges die or are constrained in their movement within some social space. We also show, using a simple epidemiological diffusion model, that a range of networks can all satisfy the small-world criterion, but behave quite differently. This demonstrates that it is problematic to generalize results across the whole space of small-world networks. © 2014 Wiley Periodicals, Inc. Complexity 19: 44–53, 2014

]]>Industrial systems can be represented as networks of organizations connected by flows of materials, energy, and money. This network context may produce unexpected consequences in response to policy intervention, so improved understanding is vital; however, industrial network data are commonly unavailable publically. Using a case study in the Humber region, UK, we present a novel methodology of “network coding” of semistructured interviews with key industrial and political stakeholders, in combination with an “industrial taxonomy” of network archetypes developed to construct an approximation of the region's networks when data are incomplete. This article describes our methodology and presents the resulting network. © 2014 Wiley Periodicals, Inc. Complexity 19: 54–72, 2014

]]>Complex social-ecological systems (SES) are not amenable to simple mathematical modeling. However, to address critical issues in SES (e.g., understanding ecological resilience/amelioration of poverty) it is necessary to describe such systems in their entirety. Based on empirical knowledge of local stakeholders and experts, we mapped their conceptions of one SES. Modelers codified what actors told us into two models: a local-level model and an overarching multiple-entity description of the system. Looking at these two representations together helps us understand links between the locally specific and other levels of decision taking and vice-versa. This “bimodeling” approach is investigated in one SES in coastal Kenya. © 2014 Wiley Periodicals, Inc. Complexity 19: 73–82, 2014

]]>A model has been developed to simulate the diffusion of energy innovations on a heterogeneous social network. Nodes on a network represent households, whose adoption of an energy innovation is based on a combination of personal and social benefit; social benefit includes the positive influence from an individual's personal social network and feedback from the wider population. This article describes the development of the model to incorporate heterogeneous parameters and, thus, become more like a real social system. The sensitivity of the model is investigated and it is shown that heterogeneity matters. This has important implications for the inclusion of real-world data into this type of model. © 2014 Wiley Periodicals, Inc. Complexity 19: 83–94, 2014

]]>Humanitarian crises and related complex emergencies caused by natural hazards or conflicts are marked by uncertainty. Disasters are extreme events mitigated through preparedness, response, and recovery. This article uses social complexity theory as a novel framework for deriving actionable insights on the onset T and severity S of disasters. Disaster distributions often show heavy tails, symptomatic of nonequilibrium dynamics, sometimes approximating a power law with critical or near-critical exponent value of 2, not “normal” (bell-shaped) or Gaussian equilibrium features. This theory-based method is applicable to existing datasets. Policy implications include the usefulness of real-time and anticipatory analytical strategies to support preparedness. © 2014 Wiley Periodicals, Inc. Complexity 19: 95–108, 2014

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