In this article, the robust state estimation problem for Markov jump genetic regulatory networks (GRNs) based on passivity theory is investigated. Moreover, the effect of time-varying delays is taken into account. The focus is on designing a linear state estimator to estimate the concentrations of the mRNAs and the proteins of the GRNs, such that the dynamics of the state estimation error can be stochastically stable while achieving the prescribed passivity performance. By applying the Lyapunov–Krasovskii functional method, delay-dependent criteria are established to ensure the existence of the mode-dependent estimator in the form of linear matrix inequalities. Based on the obtained results, the parameters of the desired estimator gains can be further calculated. Finally, a numerical example is given to illustrate the effectiveness of our proposed methods. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>On the basis of the normal intuitionistic fuzzy numbers (NIFNs), we proposed the normal interval-valued intuitionistic fuzzy numbers (NIVIFNs) in which the values of the membership and nonmembership were extended to interval numbers. First, the definition, the properties, the score function and accuracy function of the NIVIFNs are briefly introduced, and the operational laws are defined. Second, some aggregation operators based on the NIVIFNs are proposed, such as normal interval-valued intuitionistic fuzzy weighted arithmetic averaging operator, normal interval-valued intuitionistic fuzzy ordered weighted arithmetic averaging operator, normal interval-valued intuitionistic fuzzy hybrid weighted arithmetic averaging operator, normal interval-valued intuitionistic fuzzy weighted geometric averaging operator, normal interval-valued intuitionistic fuzzy ordered weighted geometric averaging operator, normal interval-valued intuitionistic fuzzy hybrid weighted geometric averaging operator, and normal interval-valued intuitionistic fuzzy generalized weighted averaging operator, normal interval-valued intuitionistic fuzzy generalized ordered weighted averaging operator, normal interval-valued intuitionistic fuzzy generalized hybrid weighted averaging operator, and some properties of these operators, such as idempotency, monotonicity, boundedness, commutativity, are studied. Further, an approach to the decision making problems with the NIVIFNs is established. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>This article investigates the robust reliable control problem for a class of uncertain switched neutral systems with mixed interval time-varying delays. The system under study involves state time-delay, parameter uncertainties and possible actuator failures. In particular, the parameter uncertainties is assumed to satisfy linear fractional transformation formulation and the involved state delay are assumed to be randomly time varying which is modeled by introducing Bernoulli distributed sequences. The main objective of this article is to obtain robust reliable feedback controller design to achieve the exponential stability of the closed-loop system in the presence of for all admissible parameter uncertainties. The proposed results not only applicable for the normal operating case of the system, but also in the presence of certain actuator failures. By constructing an appropriate Lyapunov–Krasovskii functional, a new set of criteria is derived for ensuring the robust exponential stability of the closed-loop switched neutral system. More precisely, zero inequality approach, Wirtinger's based inequality, convex combination technique and average dwell time approach are used to simplify the derivation in the main results. Finally, numerical examples with simulation result are given to illustrate the effectiveness and applicability of the proposed design approach. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>*Slime mould* Physarum polycephalum *is a single cell visible by an unaided eye. The slime mould optimizes its network of protoplasmic tubes in gradients of attractants and repellents. This behavior is interpreted as computation. Several prototypes of the slime mould computers were designed to solve problems of computation geometry, graphs, transport networks, and to implement universal computing circuits. Being a living substrate, the slime mould does not halt its behavior when a task is solved but often continues foraging the space thus masking the solution found. We propose to use temporal changes in compressibility of the slime mould patterns as indicators of the halting of the computation. Compressibility of a pattern characterizes the pattern's morphological diversity, that is, a number of different local configurations. At the beginning of computation the slime explores the space, thus generating less compressible patterns. After gradients of attractants and repellents are detected the slime spans data sites with its protoplasmic network and retracts scouting branches, thus generating more compressible patterns. We analyze the feasibility of the approach on results of laboratory experiments and computer modelling*. © 2015 Wiley Periodicals, Inc. Complexity, 2015

Modularity is a natural instrument and a ubiquitous practice for the engineering of human-made systems. However, modularization remains more of an art than a science; to the extent that the notion of optimal modularity is rarely used in engineering design. We prove that optimal modularity exists (at least for construction)—and is achieved through balanced modularization as structural symmetry in the distribution of the sizes of modules. We show that system construction cost is highly sensitive to both the number of modules and the modularization structure. However, this sensitivity has an inverse relationship with process capability and is minimal for highly capable construction processes with small process uncertainties. Conclusions are reached by a Bayesian estimation technique for a relatively simple construction model originally introduced by Herbert Simon for the hypothetical production of a linear structure, taking into account errors that may occur in the work associated with the production of the links between the nodes in the structure for varied numbers of modules. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>The problem of stabilization for wireless networked control system (NCS) with packet dropout and time delay is studied in this article. The impulsive control law for the NCS is defined with time delay and impulse. Using a switching model, the network-induced imperfections can be treated as three switching subsystems. Therein, in the case of packet dropout, the control law use the previous state via the first-order hold. The impulsive control law is designed using the switched system approach and the average dwell time method. The obtained sufficient conditions which can guarantee the exponential stability of switched system are in the form of linear matrix inequalities. Finally, a numerical example is used to demonstrate the merits and applicabilities of the proposed method. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>This article presents a new design of robust finite-time controller which replaces the traditional automatic voltage regulator for excitation control of the third-order model synchronous generator connected to an infinite bus. The effects of system uncertainties and external noises are fully taken into account. Then a single input robust controller is proposed to regulate the system states to reach the origin in a given finite time. The designed robust finite-time excitation controller can refine the system behaviors in convergence and robustness against model uncertainties and external disturbances. The robustness and finite-time stability of the closed-loop system are analytically proved using the finite-time control idea and Lyapunov stability theorem. The suitability and robustness of the designed controller are shown in contrast with two other strong nonlinear control strategies. The main advantages of the proposed controller are as follows: a) robustness against system uncertainties and external noises; b) convergence to the equilibrium point in a given finite time; and c) the use of a single control input. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>This article presents the robust dissipativity and passivity analysis of neutral-type neural networks with leakage time-varying delay via delay decomposition approach. Using delay decomposition technique, new delay-dependent criteria ensuring the considered system to be -γ dissipative are established in terms of strict linear matrix inequalities. A new Lyapunov–Krasovskii functional is constructed by dividing the discrete and neutral delay intervals into m and l segments, respectively, and choosing different Lyapunov functionals to different segments. Further, the dissipativity behaviors of neural networks which are affected due to the sensitiveness of the time delay in the leakage term have been taken into account. Finally, numerical examples are provided to show the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>In this article, the mean square exponential synchronization of a class of impulsive coupled neural networks with time-varying delays and stochastic disturbances is investigated. The information transmission among the systems can be directed and lagged, that is, the coupling matrices are not needed to be symmetrical and there exist interconnection delays. The dynamical behaviors of the networks can be both continuous and discrete. Specially, the time-varying delays are taken into consideration to describe the impulsive effects of the system. The control objective is that the trajectories of the salve system by designing suitable control schemes track the trajectories of the master system with impulsive effects. Consequently, sufficient criteria for guaranteeing the mean square exponential convergence of the two systems are obtained in view of Lyapunov stability theory, comparison principle, and mathematical induction. Finally, a numerical simulation is presented to show the verification of the main results in this article. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>The matching energy of a graph is defined as the sum of the absolute values of the zeros of its matching polynomial. For any integer t≥1, a graph G is called t-apex tree if there exists a t-set such that G − X is a tree, while for any with , G − Y is not a tree. Let be the set of t-apex trees of order n. In this article, we determine the extremal graphs from with minimal and maximal matching energies, respectively. Moreover, as an application, the extremal cacti of order n and with s cycles have been completely characterized at which the minimal matching energy are attained. © 2015 Wiley Periodicals, Inc. Complexity, 2015

]]>This article is concerned with the asymptotic stability analysis of Takagi–Sugeno stochastic fuzzy Cohen–Grossberg neural networks with discrete and distributed time-varying delays. Based on the Lyapunov functional and linear matrix inequality (LMI) technique, sufficient conditions are derived to ensure the global convergence of the equilibrium point. The proposed conditions can be checked easily by LMI Control Toolbox in Matlab. It has been shown that the results are less restrictive than previously known criteria. They are obtained under mild conditions, assuming neither differentiability nor strict monotonicity for activation function. Numerical examples are given to demonstrate the effectiveness of our results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>The solution to the game of Lights Out and its many variants have been well studied. This article introduces Langton's turmite to the game of Lights Out and discusses when Langton's turmite can solve Lights Out on a torus. The article also explores the behavior of multiple Langton's turmites on a Lights Out on a torus. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Synchronization and control of nonlinear dynamical systems with complex variables has attracted much more attention in various fields of science and engineering. In this article, we investigate the problem of impulsive synchronization for the complex-variable delayed chaotic systems with parameters perturbation and unknown parameters in which the time delay is also included in the impulsive moment. Based on the theories of adaptive control and impulsive control, synchronization schemes are designed to make a class of complex-variable chaotic delayed systems asymptotically synchronized, and unknown parameters are identified simultaneously in the process of synchronization. Sufficient conditions are derived to synchronize the complex-variable chaotic systems include delayed impulses. To illustrate the effectiveness of the proposed schemes, several numerical examples are given. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, a partial synchronization scheme is proposed based on Lyapunov stability theory to track the signal of the delay hyperchaotic Lü system using the Coullet system based on only one single controller. The proposed tracking control design has two advantages: only one controller is adopted in our approach and it can allow us to drive the hyperchaotic system to a simple chaotic system even with uncertain parameters. Numerical simulation results are given to demonstrate the effectiveness and robustness of the proposed partial synchronization scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, a new metaheuristic optimization algorithm is introduced. This algorithm is based on the ability of shark, as a superior hunter in the nature, for finding prey, which is taken from the smell sense of shark and its movement to the odor source. Various behaviors of shark within the search environment, that is, sea water, are mathematically modeled within the proposed optimization approach. The effectiveness of the suggested approach is compared with many other heuristic optimization methods based on standard benchmark functions. Also, to illustrate the efficiency of the proposed optimization method for solving real-world engineering problems, it is applied for the solution of load frequency control problem in electrical power systems. The obtained results confirm the validity of the proposed metaheuristic optimization algorithm. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, a novel sliding mode control (SMC) approach is proposed for the control of a class of underactuated systems which are featured as in cascaded form with external disturbances. The asymptotic stability conditions on the error dynamical system are expressed in the form of linear matrix inequalities. The control objective is to construct a controller such that would force the state trajectories to approach the sliding surface with an exponential policy. The proposed SMC has a simple structure because it is derived from the associated first-order differential equation and is capable of handling system disturbances and nonlinearities. The effectiveness of the proposed control method is validated using intensive simulations. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This study estimates the parameters of a power law fit of the distribution of log returns of exchange traded funds (ETFs) before, during, and after the recent financial crisis. It is found, that there is considerable variation both between ETFs and between calm and turbulent phases. Exponents of the daily log return distribution are estimated to lie mostly between 3.0 and 5.0 depending on the ETF. In minute-by-minute, trading data much lower power law exponents have been found concentrating between 3.0 and 4.0 and sometimes dropping to values close to or below 3.0. Further, there is evidence for changes in the distribution during times of turbulence (value of the exponent, improvement in the goodness of fit measures of the distribution). It can be hypothesized that effects such as, infinite variance (for α < 3) or changes in the form of the distribution can occur, in turn affecting the predictability of the system which has implications for the possibility to control or regulate financial markets under such conditions. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Current research on pedestrian dynamics mainly focuses on the interactions among isolated individuals, the impact of the presence of groups is not fully considered. In recent 5 years, researchers have started to investigate pedestrian group movement. The aim of this work is to explore the local behavior of pedestrian groups by questionnaires and field observation. Survey study focused on pedestrians' psychology when walking in groups, which included five parts: group size, interpersonal distance, spatial relationship among group members, speed adjustment of group members, information transmission, and acid action among group members. Meantime a field observation was carried out to study group movement characteristics, which contained speed, step frequency, offset angle and interpersonal distance. The survey results show that group members have a closer interpersonal distance, faster information transmission and plenty of acid action. Conversely, group walking has a negative influence on pedestrian's speed, step frequency by comparing with the way isolated pedestrian walks. In addition, it is found that for a certain group, the group members are able to keep movement consistent. Also there exists obvious movement diversity among different group types (male dyads, female dyads, couple groups, and ordinary-friend groups) because of different gender and social relationship. Ultimately the results will be more promising for helping to model the movement of pedestrian groups. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article discusses the issue of robust stability analysis for a class of Markovian jumping stochastic neural networks (NNs) with probabilistic time-varying delays. The jumping parameters are represented as a continuous-time discrete-state Markov chain. Using the stochastic stability theory, properties of Brownian motion, the information of probabilistic time-varying delay, the generalized Ito's formula, and linear matrix inequality (LMI) technique, some novel sufficient conditions are obtained to guarantee the stochastical stability of the given NNs. In particular, the activation functions considered in this article are reasonably general in view of the fact that they may depend on Markovian jump parameters and they are more general than those usual Lipschitz conditions. The main features of this article are described in the following: first one is that, based on generalized Finsler lemma, some improved delay-dependent stability criteria are established and the second one is that the nonlinear stochastic perturbation acting on the system satisfies a class of Lipschitz linear growth conditions. By resorting to the Lyapunov–Krasovskii stability theory and the stochastic analysis tools, sufficient stability conditions are established using an efficient LMI approach. Finally, two numerical examples and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>An exploratory study is made on the dynamics of the map defining the Mandelbrot set endowed with memory (m) of past iterations, that is, , . © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article investigates the adaptive impulsive synchronization of delayed chaotic system with full unknown parameters. Aiming at this problem, we propose a new adaptive strategy, in which both the adaptive–impulsive controller and the parameters adaptive laws are designed via the discrete-time signals from the drive system. The corresponding theoretical proof is given to guarantee the effectiveness of the proposed strategy. Moreover, the concrete adaptive strategies are achieved for delayed Hopfield neural network, optical Ikeda system and the well-known delayed Lü chaotic system. As expected, numerical simulations show the effectiveness of the proposed strategy. This method has potential applications in parameters estimation, secure communication, and cryptanalysis when only discrete signals are transmitted in communication channel. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Filtration combustion (FC) is described by Laplacian growth without surface tension. These equations have elegant analytical solutions that replace the complex integro-differential motion equations by simple differential equations of pole motion in a complex plane. The main problem with such a solution is the existence of finite time singularities. To prevent such singularities, nonzero surface tension is usually used. However, nonzero surface tension does not exist in FC, and this destroys the analytical solutions. However, a more elegant approach exists for solving the problem. First, we can introduce a small amount of pole noise to the system. Second, for regularization of the problem, we throw out all new poles that can produce a finite time singularity. It can be strictly proved that the asymptotic solution for such a system is a single finger. Moreover, the qualitative consideration demonstrates that a finger with of the channel width is statistically stable. Therefore, all properties of such a solution are exactly the same as those of the solution with nonzero surface tension under numerical noise. The solution of the Saffman–Taylor problem without surface tension is similar to the solution for the equation of cellular flames in the case of the combustion of gas mixtures. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>To analyze the complexity of continuous chaotic systems better, the modified multiscale permutation entropy (MMPE) algorithm is proposed. Characteristics and parameter choices of the MMPE algorithm are investigated. The comparative study between MPE and MMPE shows that MMPE has better robustness for identifying different chaotic systems when the scale factor τ takes large values. Compared with MPE, MMPE algorithm is more suitable for analyzing the complexity of time series as it has τ time series. For its application, MMPE algorithm is used to calculate the complexity of multiscroll chaotic systems. Results show that complexity of multiscroll chaotic systems does not increase as scroll number increases. Discussions based on first-order difference operation present a reasonable explanation on why the complexity does not increase. This complexity analysis method lays a theoretical as well as experimental basis for the applications of multiscroll chaotic systems. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>We work on a model that has succeeded in describing real cases of coexistence of two languages within a closed community of speakers, taking into account bilingualism and incorporating a parameter to measure the distance between languages. The dynamics of this model depend on a characteristic exponent, which weighs the power of the size of a group of speakers to attract new members. So far, this model had been solved only when this characteristic exponent is greater than 1. In this article, we have managed to solve the nature of the stability of all the possible situations for this characteristic exponent, that is, when it is less or equal than 1 and covering also the situations produced when it is 0 or negative. We interpret these new situations and find that, even in such exotic scenarios, there are configurations of the resulting societies where all the languages coexist. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article addresses stability analysis of a general class of memristor-based complex-valued recurrent neural networks (MCVNNs) with time delays. Some sufficient conditions to guarantee the boundedness on a compact set that globally attracts all trajectories of the MCVNNs are obtained by utilizing local inhibition. Moreover, some sufficient conditions for exponential stability and the global stability of the MCVNNs are established with the help of local invariant sets and linear matrix inequalities using Lyapunov–Krasovskii functional. The analysis results in the article, based on the results from the theory of differential equations with discontinuous right-hand sides as introduced by Filippov. Finally, two numerical examples are also presented to show the effectiveness and usefulness of our theoretical results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This manuscript analyzed the delay-dependent stability problem for non-linear switched singular time-delay systems based on average dwell time and delay decomposition approach. Both cases of time-delays namely constant and time-varying delays are treated in the switched singular systems. Based on piecewise Lyapunov–Krasovskii functional, linear matrix inequality technique and an average dwell time approach, sufficient conditions which ensures that the delay-dependent exponential stability conditions for uncertain switched singular systems are discussed. Finally, numerical examples and simulations are provided to demonstrate the effectiveness of the proposed techniques. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article investigates the problem of reliable mixed control for discrete-time interval type-2 (IT2) fuzzy model-based systems via static output-feedback (SOF) control method. The number of fuzzy rules and the membership functions for the SOF controller are different from those for the plant. A sufficient criterion of reliable stability with mixed performance is derived for the closed-loop system with sensor failure. The SOF controller is designed for two different cases (known sensor failure case and unknown sensor failure case) to guarantee the reliable stability with mixed performance. Moreover, novel criteria are presented to obtain the optical performance for the closed-loop system. Finally, an example is used to verify the effectiveness of the proposed design scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>The significant characteristic of the TODIM (an acronym in Portuguese of Interactive and Multiple Attribute Decision Making) method is that it can consider the bounded rationality of the decision makers. However, in the classical TODIM method, the rating of the attributes only can be used in the form of crisp numbers. Because 2-dimension uncertain linguistic variables can easily express the fuzzy information, in this article, we extend the TODIM method to 2-dimension uncertain linguistic information. First of all, the definition, characteristics, expectation, comparative method and distance of 2-dimension uncertain linguistic information are introduced, and the steps of the classical TODIM method for Multiple attribute decision making (MADM) problems are presented. Second, on the basis of the classical TODIM method, the extended TODIM method is proposed to deal with MADM problems in which the attribute values are in the form of 2-dimension uncertain linguistic variables, and detailed decision steps are given. Its significant characteristic is that it can fully consider the bounded rationality of the decision makers, which is a real action in real decision making. Finally, a numerical example is provided to verify the developed approach and its practicality and effectiveness. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Artificial, neurobiological, and social networks are three distinct complex adaptive systems (CASs), each containing discrete processing units (nodes, neurons, and humans, respectively). Despite the apparent differences, these three networks are bound by common underlying principles which describe the behavior of the system in terms of the connections of its components, and its emergent properties. The longevity (long-term retention and functionality) of the components of each of these systems is also defined by common principles. Here, I will examine some properties of the longevity and function of the components of artificial and neurobiological systems, and generalize these to the longevity and function of the components of social CAS. In other words, I will show that principles governing the long-term functionality of computer nodes and of neurons, may be extrapolated to the study of the long-term functionality of humans (or more precisely, of the noemes, an abstract combination of “existence” and “digital fame”). The study of these phenomena can provide useful insights regarding practical ways that can be used to maximize human longevity. The basic law governing these behaviors is the “Law of Requisite Usefulness,” which states that the length of retention of an agent within a CAS is proportional to the agent's contribution to the overall adaptability of the system. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article is concerned with the boundedness solutions of the brushless DC motor system. For this system, the global attractive set and positively invariant set are obtained based on generalized Lyapunov function stability theory and the extremum principle of function. Furthermore, the rate of the trajectories is also obtained. Numerical simulations are presented to show the effectiveness of the proposed scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article investigates the sliding mode control method for a class of chaotic systems with matched and unmatched uncertain parameters. The proposed reaching law is established to guarantee the existence of the sliding mode around the sliding surface in a finite-time. Based on the Lyapunov stability theory, the conditions on the state error bound are expressed in the form of linear matrix inequalities. Simulation results for the well-known Genesio's chaotic system are provided to illustrate the effectiveness of the proposed scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Decisions on settlement location in the face of climate change and coastal inundation may have resulted in success, survival or even catastrophic failure for early settlers in many parts of the world. In this study, we investigate various questions related to how individuals respond to a palaeoenvironmental simulation, on an interactive tabletop device where participants have the opportunity to build a settlement on a coastal landscape, balancing safety, and access to resources, including sea and terrestrial foodstuffs, while taking into consideration the threat of rising sea levels. The results of the study were analyzed to consider whether decisions on settlement were predicated to be near to locations where previous structures were located, stigmergically, and whether later settler choice would fare better, and score higher, as time progressed. The proximity of settlements was investigated and the reasons for clustering were considered. The interactive simulation was exhibited to thousands of visitors at the 2012 Royal Society Summer Science Exhibition at the “Europe's Lost World” exhibit. 347 participants contributed to the simulation, providing a sufficiently large sample of data for analysis. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>A novel variable structure and disturbance rejection control strategy for a wind turbines equipped with a double fed induction generator based on stator-flux-oriented vector control is presented. According to estimation of maximum power operation points of wind turbine under stochastic wind velocity profiles and tracking them using traditional offline gain, scheduling and innovative adaptive online method is necessary. To demonstrate the effectiveness of the proposed control strategy, the estimation of maximum operating power point of wind turbine and tracking it under stochastic wind velocity profiles has been considered as a test case. Simulation results show the validity of the proposed technique. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article presents a new approach to economic load dispatch (ELD) problems by the considering the cost functions, impact renewable energy as wind turbin and subsidies. Economic dispatch is the short-term determination of the optimal output of a number of electricity generation facilities, to meet the system load, at the lowest possible cost, subject to transmission and operational constraints. The main goal in the deregulated system is subsidies and analysis performance on government to minimize the total fuel cost while satisfying the load demand and operational constraints. The practical ELD problems have nonsmooth cost functions with equality and inequality constraints, which make the problem of finding the global optimum difficult when using any mathematical approaches. Accordingly, particle swarm optimization with time-varying inertia weight (PSO-TVIW) used for solving this problem. The effectiveness of the proposed strategy is applied over real-world engineering problem and highly constrained. Obtained results indicate that PSO-TVIW can successfully solve this problem. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, we consider the problem of robust dissipativity and passivity analysis for a class of general discrete-time recurrent neural networks (NNs) with time-varying delays. The NN under consideration is subject to time-varying and norm bounded parameter uncertainties. By the latest free-weighting matrix method, an appropriate Lyapunov–Krasovskii functional and using stochastic analysis technique a sufficient condition is established to ensure that the NNs under consideration is strictly -dissipative. The derived conditions are presented in terms of linear matrix inequalities. Numerical examples and its simulations are given to demonstrate the effectiveness of the results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, the problem of robust tracking control for a class of uncertain Markovian jump systems with interval time-varying delay is investigated. Based on an augmented Lyapunov–Krasovskii functional with triple integral term, partitioning the delay's lower bound and reciprocally convex approach, delay-dependent conditions for the existence of desired controller are achieved. Meanwhile, stability criteria for delayed Markovian jump systems are also provided with less conservativeness and less matrix variables than some recent results. Finally, two simulation examples are given to illustrate the effectiveness of the proposed design method. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>One of the most important objectives of electricity distribution companies is to improve the reliability of the distribution networks. To this end, the electricity distribution companies try to optimally use the existing financial resources in the planning of preventive maintenance (PM) programs to reduce the imposed costs on the system due to the failure of network components and to improve the network reliability. In fuzzy analytical hierarchical process (fuzzy AHP) method, the degree of network reliability and the effectiveness of PM budget in the improvement of network reliability are selected as decision criteria in the budget allocation procedure. The areas served by the power distribution network are prioritized relative to each other and are assigned weights based on these priorities. The PM budget is determined based on the obtained weights. The medium voltage distribution network of seven areas in the city of Tehran have been selected for the implementation of the proposed method and the analysis of the obtained results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article introduces a way of measuring the intrinsic complexity of models. Unlike complication, complexity is an irreducible indication of the innate characteristics of models. Instead of a reductionist paradigm, complexity should be measured in a holistic way. This article redefines the relationship between models and data, and proposes the concept of the “weight” of models, that is, how “heavy” a model is. Based on this concept, this article further defines the complexity of a model to be its ability to distort the space configuration. Three complexity indices are proposed to quantify the extent to which the input space is distorted by a model. It is recognized that there is a lack of widely accepted definition or measure of model complexity. The answer provided by this article is an attempt to move the inquiry a step closer to that goal. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article presents an adaptive sliding mode control (SMC) scheme for the stabilization problem of uncertain time-delay chaotic systems with input dead-zone nonlinearity. The algorithm is based on SMC, adaptive control, and linear matrix inequality technique. Using Lyapunov stability theorem, the proposed control scheme guarantees the stability of overall closed-loop uncertain time-delay chaotic system with input dead-zone nonlinearity. It is shown that the state trajectories converge to zero asymptotically in the presence of input dead-zone nonlinearity, time-delays, nonlinear real-valued functions, parameter uncertainties, and external disturbances simultaneously. The selection of sliding surface and the design of control law are two important issues, which have been addressed. Moreover, the knowledge of upper bound of uncertainties is not required. The reaching phase and chattering phenomenon are eliminated. Simulation results demonstrate the effectiveness and robustness of the proposed scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>Unintended effects are well known to economists and sociologists and their consequences may be devastating. The main objective of this article is to formulate a mathematical theorem, based on Gödel's famous incompleteness theorem, in which it is shown, that from the moment deontical modalities (prohibition, obligation, permission, and faculty) are introduced into the social system, responses are allowed by the system that are not produced, however, prohibited responses or unintended effects may occur. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article investigates the control problem for polynomial fuzzy discrete-time systems. Signal quantization is considered in this article. To deal with this issue, a logarithmic quantizer is adopted to quantize the control signal. First, a novel method is first proposed to model polynomial fuzzy discrete-time systems and handle the quantized control problem of the systems. Second, based on Lyapunov-stability theory, sufficient conditions are obtained in terms of sum of squares to guarantee the asymptotical stability of the systems and satisfy a performance. Finally, a simulation example is given to illustrate the effectiveness of the proposed results. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>The mathematical viability theory proposes methods and tools to study at a global level how controlled dynamical systems can be confined in a desirable subset of the state space. Multilevel viability problems are rarely studied since they induce combinatorial explosion (the set of *N* agents each evolving in a *p*-dimensional state space, can evolve in a *Np* dimensional state space). In this article, we propose an original approach which consists in solving first local viability problems and then studying the real viability of the combination of the local strategies, by simulation where necessary. In this article, we consider as multilevel viability problem a stylized agricultural cooperative which has to keep a minimum of members. Members have an economical constraint and some members have a simple model of the functioning of the cooperative and make assumptions on other members' behavior, especially proviable agents which are concerned about their own viability. In this framework, the model assumptions allow us to solve the local viability problem at the agent level. At the cooperative level, considering mixture of agents, simulation results indicate if and when including proviable agents increases the viability of the whole cooperative. © 2014 Wiley Periodicals, Inc. Complexity, 2014

This article investigates the function projective synchronization (FPS) for a class of time-delay chaotic system via nonlinear adaptive-impulsive control. To achieve the FPS, suitable nonlinear continuous and impulsive controllers are designed based on adaptive control theory and impulsive control theory. Using the generalized Babarlat's lemma, a general condition is given to ensure the FPS. Here, the time-delay chaotic system is assumed to satisfy the Lipschitz condition while the Lipschitz constants are estimated by augmented adaptation equations. Numerical simulation results are also presented to verify the effectiveness of the proposed synchronization scheme. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, a passive neurowavelet based on islanding detection technique for grid-connected inverter-based distributed generation has been developed. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem-free. Unintentional islanding is one of the encountered problems. Islanding is the situation where the distribution system containing both distributed generator and loads is separated from the main grid as a result of many reasons such as electrical faults and their subsequent switching incidents, equipment failures, or preplanned switching events like maintenance. The proposed method utilizes and combines wavelet analysis and artificial neural network to detect islanding. Discrete wavelet transform is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. Passive schemes have a large nondetection zone (NDZ) and concern has been raised on active method due to its degrading power quality effect. 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. The simulations results, performed by MATLAB/Simulink, shows that the proposed method has a small NDZ. Also, this method is capable of detecting islanding accurately within the minimum standard time. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article studies the problem of observer-based dissipative control problem for wireless networked control systems (NCSs). The packet loss and time delay in the network are modeled by a set of switches, using that a discrete-time switched system is formulated. First, results for the exponential dissipativity of discrete-time switched system with time-varying delays are proposed by using the average dwell time approach and multiple Lyapunov–Krasovskii function. Then, the results are extended to drive the controller design for considered wireless NCS. The attention is focused on designing an observer-based state feedback controller which ensures that, for all network-induced delay and packet loss, the resulting error system is exponentially stable and strictly dissipative. The sufficient conditions for existence of controllers are formulated in the form of linear matrix inequalities (LMIs), which can be easily solved using some standard numerical packages. Both observer and controller gains can be obtained by the solutions of set of LMIs. Finally, numerical examples are provided to illustrate the applicability and effectiveness of the proposed method. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>We have derived time evolution equations for thermodynamic systems with correlated states, considering the change in a probability density, entropy, and phase space metric at fixed phase-space locations and obtained simple relations between these quantities for the separate systems. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>In this article, the assessment of new coordinated design of power system stabilizers (PSSs) and static var compensator (SVC) in a multimachine power system via statistical method is proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The bacterial swarming optimization (BSO), which synergistically couples the bacterial foraging with the particle swarm optimization (PSO), is used to seek for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is enhanced. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO-based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is executed to validate the robustness of coordinated controller versus uncoordinated one. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article investigates the finite-time stability, stabilization, and boundedness problems for switched nonlinear systems with time-delay. Unlike the existing average dwell-time technique based on time-dependent switching strategy, largest region function strategy, that is, state-dependent switching control strategy is adopted to design the switching signal, which does not require the switching instants to be given in advance. Some sufficient conditions which guarantee finite-time stable, stabilization, and boundedness of switched nonlinear systems with time-delay are presented in terms of linear matrix inequalities. Detail proofs are given using multiple Lyapunov-like functions. A numerical example is given to illustrate the effectiveness of the proposed methods. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>A novel hybrid approach involving particle swarm optimization (PSO) and bacterial foraging optimization algorithm (BFOA) called bacterial swarm optimization (BSO) is illustrated for designing static var compensator (SVC) in a multimachine power system. In BSO, the search directions of tumble behavior for each bacterium are oriented by the individual's best location and the global best location of PSO. The proposed hybrid algorithm has been extensively compared with the original BFOA algorithm and the PSO algorithm. Simulation results have shown the validity of the proposed BSO in tuning SVC compared with BFOA and PSO. Moreover, the results are presented to demonstrate the effectiveness of the proposed controller to improve the power system stability over a wide range of loading conditions. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>This article investigates a novel fast terminal sliding mode control approach combined with global sliding surface structure for the robust tracking control of nonlinear second-order systems with time-varying uncertainties. The suggested control technique is formulated based on the Lyapunov stability theory and guarantees the existence of the sliding mode around the sliding surface in a finite time. Using the new form of switching surface, the reaching phase elimination and the robustness improvement of the whole system are satisfied. Simulation results demonstrate the efficiency of the proposed technique. © 2014 Wiley Periodicals, Inc. Complexity, 2014

]]>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

]]>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 20: 12–21, 2015

]]>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 20: 22–38, 2015

In this article, an exponential stability analysis of Markovian jumping stochastic bidirectional associative memory (BAM) neural networks with mode-dependent probabilistic time-varying delays and impulsive control is investigated. By establishment of a stochastic variable with Bernoulli distribution, the information of probabilistic time-varying delay is considered and transformed into one with deterministic time-varying delay and stochastic parameters. By fully taking the inherent characteristic of such kind of stochastic BAM neural networks into account, a novel Lyapunov-Krasovskii functional is constructed with as many as possible positive definite matrices which depends on the system mode and a triple-integral term is introduced for deriving the delay-dependent stability conditions. Furthermore, mode-dependent mean square exponential stability criteria are derived by constructing a new Lyapunov-Krasovskii functional with modes in the integral terms and using some stochastic analysis techniques. The criteria are formulated in terms of a set of linear matrix inequalities, which can be checked efficiently by use of some standard numerical packages. Finally, numerical examples and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results. © 2014 Wiley Periodicals, Inc. Complexity 20: 39–65, 2015

]]>This article describes the use of grammatical evolution to obtain a predator–prey ecosystem of artificial beings associated with mathematical functions, whose fitness is also defined mathematically. The system supports the simultaneous evolution of several ecological niches and through the use of standard measurements, makes it possible to explore the influence of the number of niches and the values of several parameters on “biological” diversity and similar functions. Sensitivity analysis tests have been made to find the effect of assigning different constant values to the genetic parameters that rule the evolution of the system and the predator–prey interaction or of replacing them by functions of time. One of the parameters (predator efficiency) was found to have a critical range, outside which the ecologies are unstable; two others (genetic shortening rate and predator–prey fitness comparison logistic amplitude) are critical just at one side of the range), the others are not critical. The system seems quite robust, even when one or more parameters are made variable during a single experiment, without leaving their critical ranges. Our results also suggest that some of the features of biological evolution depend more on the genetic substrate and natural selection than on the actual phenotypic expression of that substrate. © 2014 Wiley Periodicals, Inc. Complexity 20: 66–83, 2015

]]>This study's aim is to analyze heart rate dynamics in subjects with diabetes by measures of heart rate variability (HRV). The correlation of chaotic global parameters in the two cohorts is able to assess the probability of cardiac failure and other dynamical diseases. Adults (46) were divided into two equal groups. The autonomic evaluation consisted of measuring HRV for 30 min in supine position in absence of any physical, sensory, or pharmacological stimuli. Chaotic global parameters are able to statistically determine which series of electrocardiograph interpeak intervals in short time-series are diabetic and which are not. The chaotic forward parameter that applies all three parameters is suggested to be the most appropriate and robust algorithm. This was decided after tests for normality; followed by one-way analysis of variance (ANOVA1); (P < 0.09) and Kruskal–Wallis technique (P < 0.03). Principal component analysis implied two components represent 99.8% of total variance. Therefore, diabetes is a disease which reduces the chaotic response and, as such may be termed a dynamical condition such as are cardiac arrest, asthma, and epilepsy. © 2014 Wiley Periodicals, Inc. Complexity 20: 84–92, 2015

]]>