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

]]>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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