Showing papers in "Complexity in 2014"

Robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties

Abstract: The problem of robust decentralized adaptive synchronization of general complex networks with coupling delayed and uncertainties is investigated in this article. It is only assumed that the upper normal bound of uncertain inner and outer coupling matrices is positive but its concrete structure is not also required to be known. The time-varying coupling delay is a any nonnegative continuous and bounded function and not require its derivative to be less than one, that is, general time-varying coupling delays and uncertainties. For such a class of uncertain complex networks, a new synchronization scheme is presented by a class of continuous memoryless robust decentralized adaptive synchronization controllers. It is also shown that the synchronization error dynamics of uncertain complex networks can be guaranteed as uniformly exponentially convergent toward a ball that can be as small as desired. Finally, numerical simulations are provided to demonstrate the effectiveness and robustness of proposed complex networks synchronization schemes. © 2013 Wiley Periodicals, Inc. Complexity 19: 10–26, 2014

A new multiobjective allocator of capacitor banks and distributed generations using a new investigated differential evolution

Abstract: This article has investigated a new multiobjective allocation of optimal sizing and sitting of distributed generation DG units and capacitor banks in simultaneous mode to improve reliability and reduce energy losses. The proposed method consists of four objectives, that is, cost of energy not supplied, system average interruption duration index, costs of energy loss and investment. A novel structure differential evolution has been suggested to solve this nonlinear complex problem and its results are compared with related values of genetic algorithm and simple differential evolutionary algorithm. In addition to the novel objective function, the other contribution of this article is proposing a new model for load and energy cost. Three types of DGs, that is, wind turbine, solar cell, and diesel generator have been used in placement process. To verify the comprehensiveness of the proposed function, three scenarios have been introduced: scenario i: first, placement of DGs, then capacitor banks, scenario ii: first, placement of capacitor banks, and then DGs, and scenario iii: simultaneous placement of DGs and capacitor banks. Simulations have been carried out on one part of practical distribution network in Metropolitan Tabriz in North West of Iran. The results of simulations have been discussed and analyzed using the five novel indices. The obtained simulation results using proposed function shows that the simultaneous placement of DGs and capacitor banks results in more reduction of the energy losses and increase improvements of reliability indices as well as voltage profile. © 2013 Wiley Periodicals, Inc. Complexity 19: 40-54, 2014

Chaotic fractional-order model for muscular blood vessel and its control via fractional control scheme

Abstract: This article studies the chaotic and complex behavior in a fractional-order biomathematical model of a muscular blood vessel MBV. It is shown that the fractional-order MBV FOMBV model exhibits very complex and rich dynamics such as chaos. We show that the corresponding maximal Lyapunov exponent of the FOMBV system is positive which implies the existence of chaos. Strange attractors of the FOMBV model are depicted to validate the chaotic behavior of the system. We change the fractional order of the model and investigate the dynamics of the system. To suppress the chaotic behavior of the model, we propose a single input fractional finite-time controller and prove its stability using the fractional Lyapunov theory. In addition, the effects of the model uncertainties and external disturbances are taken into account and a robust fractional finite-time controller is constructed. The upper bound of the chaos suppression time is also given. Some computer simulations are presented to illustrate the findings of this article. © 2014 Wiley Periodicals, Inc. Complexity 20: 37-46, 2014

Parameters estimation, mixed synchronization, and antisynchronization in chaotic systems

Abstract: Mixed synchronization between two Hindmarsh-Rose neuron models is realized by optimizing the scheme of Lyapunov function with two selectable gain coefficients. Based on the Lyapunov stability theory, the distribution of synchronization region and the nonsynchronization region in the two-parameter phase space is calculated, respectively. And then the optimized parameter observers and controllers are approached analytically. All unknown parameters with different orders of magnitude are identified accurately, and the error function for corresponding variables decreases to stable value when the two gain coefficients are given values in the synchronization region. Otherwise, only the four larger unknown parameters are estimated exactly and the error function of corresponding variables decreases stably to certain minimal value with an order about 1 × 10-6, whereas the smallest unknown parameter is approached greatly although the error of corresponding variables are stabilized within certain transient period. © 2014 Wiley Periodicals, Inc. Complexity 20: 64-73, 2014

State estimation of memristor-based recurrent neural networks with time-varying delays based on passivity theory

Abstract: This article deals with the state estimation problem of memristor-based recurrent neural networks MRNNs with time-varying delay based on passivity theory The main purpose is to estimate the neuron states, through available output measurements such that for all admissible time delay, the dynamics of the estimation error is passive from the control input to the output error Based on the Lyapunov-Krasovskii functional LKF involving proper triple integral terms, convex combination technique, and reciprocal convex technique, a delay-dependent state estimation of MRNNs with time-varying delay is established in terms of linear matrix inequalities LMIs The information about the neuron activation functions and lower bound of the time-varying delays is fully used in the LKF Then, the desired estimator gain matrix is accomplished by solving LMIs Finally, a numerical example is provided to demonstrate the effectiveness of the proposed theoretical results © 2013 Wiley Periodicals, Inc Complexity 19: 32-43, 2014

Leader-following consensus problem of heterogeneous multi-agent systems with nonlinear dynamics using fuzzy disturbance observer

Abstract: This article considers the leader-following consensus problem of heterogeneous multi-agent systems The proposed multi-agent system is consisted of heterogeneous agents where each agents have their own nonlinear dynamic behavior To overcome difficulty from heterogeneous nonlinear intrinsic dynamics of agents, a fuzzy disturbance observer is adopted In addition, based on the Lyapunov stability theory, an adaptive control method is used to compensate the observation error caused by the difference between the unknown factor and estimated values Two numerical examples are given to illustrate the effectiveness of the proposed method © 2013 Wiley Periodicals, Inc Complexity 19: 20-31, 2014

A new multiobjective procedure for solving nonconvex environmental/economic power dispatch

Abstract: In this article, an improved multiobjective chaotic interactive honey bee mating optimization CIHBMO is proposed to find the feasible optimal solution of the environmental/economic power dispatch problem with considering operational constraints of the generators. The three conflicting and noncommensurable: fuel cost, pollutant emissions, and system loss, should be minimized simultaneously while satisfying certain system constraints. To achieve a good design with different solutions in a multiobjective optimization problem, Pareto dominance concept is used to generate and sort the dominated and nondominated solutions. Also, fuzzy set theory is used to extract the best compromise solution. The propose method has been individually examined and applied to the standard Institute of Electrical and Electronics Engineers IEEE 30-bus six generator, IEEE 180-bus 14 generator and 40 generating unit with valve point effect test systems. The computational results reveal that the multiobjective CIHBMO algorithm has excellent convergence characteristics and is superior to other multiobjective optimization algorithms. Also, the result shows its great potential in handling the multiobjective problems in power systems. © 2014 Wiley Periodicals, Inc. Complexity 20: 47-62, 2014

Multiobjectives bihistogram equalization for image contrast enhancement

Abstract: The global histogram equalization HE has been the most frequently adopted image contrast enhancement technique. A brightness and detail-preserving HE method with good contrast enhancement effect has been a goal of much recent research in HE. Nevertheless, producing a well-balanced HE is deemed to be a daunting task. In this article, we propose a novel framework of HE with the aim of taking three desirable properties into account: brightness preservation, detail preservation, and contrast enhancement. We termed the proposed method as multipurpose beta optimized bi-HE MBOBHE. MBOBHE consists of performing the histogram optimization separately in both subhistograms after the segmentation of histogram using an optimized separating point based on the three performance criteria using a weighted-sum aggregated objective function AOF. Both quantitative and qualitative results indicate that MBOBHE outperforms other existing bi-HE methods, in terms of comprehensive performance of HE that is capable of providing a holistic view. © 2014 Wiley Periodicals, Inc. Complexity 20: 22-36, 2014

Modeling social-ecological problems in coastal ecosystems: A case study

Abstract: 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

Complexity at the social science interface

Abstract: 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

A social science-inspired complexity policy: Beyond the mantra of incentivization

Abstract: 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

Myth, language, and complex ideologies

Abstract: Ideologies use for their conservation and propagation persuasive methods of communication: rhetoric. Rhetoric is analyzed from the semiotic and logical-mathematical points of view. The following hypotheses are established: 1 language L is a self-explanatory system, mediated by a successive series of systems of cultural conventions, 2 connotative significances of an ideological advertising rhetoric must be known, and 3 the notion of ideological information is a neutral notion that does not imply the valuation of ideology or its conditions of veracity or falsification. Rhetorical figures like metonymy, metaphor, parable analogy, and allegory are defined as relations. Metaphor and parable are order relations. Operations of metonymic and metaphoric substitution are defined and several theorems derived from these operations have been deduced. © 2014 Wiley Periodicals, Inc. Complexity 20: 63-81, 2014

Language-like behavior of protein length distribution in proteomes

Abstract: In this study, to demonstrate the language-like behavior of protein length distribution in proteomes, a quantitative linguistic distribution model, Menzerath-Altmann model, was adopted. A total of 10 proteomes from completely sequenced representative organisms archaea, bacteria, and eukarya domains were examined. The results showed that the protein length distribution in the complete set of proteomic proteins, or at least in a wide range for each proteome, can be described reasonably well using the distribution model without considering any complex underlying mechanisms. The deliberation of the model parameters confirmed the evolutionary trend and the model parameters were observed to be related to organismal complexity. © 2014 Wiley Periodicals, Inc. Complexity 20: 12-21, 2014

Dynamic, small-world social network generation through local agent interactions

Abstract: 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

Exponential state estimator design for discrete-time neural networks with discrete and distributed time-varying delays

Abstract: In this article, the probl of state estimation for discrete-time neural networks with mixed time-varying delays is investigated. The mixed time delays consist of both discrete and distributed delays. An appropriate Lyapunov-Krasovskii functional put forward to reflect the mixed time-varying delays is proposed to establish sufficient conditions for the existence of admissible state estimators. The conditions are described in the form of linear matrix inequalities LMIs, which guarantee the estimation error to be globally exponentially stable in the presence of mixed time-varying delays. Then, the desired estimator matrix gain can be characterized in terms of the solution to these LMIs. A numerical example is addressed to show the effectiveness of the proposed design method. © 2014 Wiley Periodicals, Inc. Complexity 20: 38-48, 2014

A theorical point of view of reality, perception, and language

Abstract: It is possible to view the relations between mathematics and natural language from different aspects. This relation between mathematics and language is not based on just one aspect. In this article, the authors address the role of the Subject facing Reality through language. Perception is defined and a mathematical theory of the perceptual field is proposed. The distinction between purely expressive language and purely informative language is considered false, because the subject is expressed in the communication of a message, and conversely, in purely expressive language, as in an exclamation, there is some information. To study the relation between language and reality, the function of ostensibility is defined and propositions are divided into ostensives and estimatives. © 2013 Wiley Periodicals, Inc. Complexity 20: 27-37, 2014

Modeling diffusion of energy innovations on a heterogeneous social network and approaches to integration of real-world data

Abstract: 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

Entrepreneurship and the emergence of industrial clusters

Abstract: 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

Exponential growth in Ebola outbreak since May 14, 2014

Abstract: C ontrary to general opinion, the current Ebola outbreak in West Africa followed an exponential growth curve starting already in mid-May. The death toll followed an exponential growth curve with almost the same time constant , allowing direct calculation of the mortality of the outbreak. This value remained steady at about 72%, contrary to the estimate of the World Health Organization of slightly above 50%. Until the last 2 weeks, the projected date at which the number of infected individuals would reach 100,000 had remained steady at January 19. Updated statistics from September 6 advanced that date by at least a month. Estimates suggest that over 20,000 already have been infected, exceeding the number that the WHO has declared could be the eventual outcome. The statistics of the Ebola outbreak in western Africa, as reported by the World Health Organization (WHO), has gone through three phases, as shown in Figure 1, and may be entering a fourth. The first several months saw a relatively rapid increase, followed by a period of about 6 weeks when the disease appeared to be under control. But from the end of May to the end of August, the outbreak followed an almost ideal exponential growth rate. With such unambiguous statistics, several conclusions could be drawn that need rapid transmission. First, however, some basic results from previous Ebola epidemics are introduced in order to provide a context for discussion. Although the incubation period of Ebola is known to range from 2 to 21 days [1, 2], the typical incubation period is 8–10 days. When fatal, death usually occurs between 7 and 16 days, and most often between 8 and 9 days [3] after the onset of symptoms. When not fatal, the acute phase typically lasts 14–16 days [3]. Thus, in cases where death is the outcome, the typical course of the disease is approximately 17–18 days, and when the patient recovers, about 24 days. The disease can be transmitted at any time when symptoms are apparent. Further, fluids from the human body remain contagious some additional days past death, allowing infection of other individuals posthumously, which does occur for a variety of reasons, including respectful handling of the body. A typical period between diagnosis of a primary case and a secondary case is thus a mean incubation period (10 days) plus some fraction, perhaps half of the period the individual remains infectious (roughly an additional …

Toward a formalism of modeling and simulation using model theory

Abstract: This article proposes a Modeling and Simulation (M&S) formalism using Model Theory. The article departs from the premise that M&S is the science that studies the nature of truth using models and simulations. Truth in models and simulations is relative as they seek to answer specific modeling questions. Consequently, truth in M&S is relative because every model is a purposeful abstraction of reality. We use Model Theory to express the proposed formalism because it is built from the premise that truth is relative. The proposed formalism allows us to: (1) deduce formal definitions and explanations of areas of study in M&S, including conceptual modeling, validity, and interoperability, and (2) gain insight into which tools can be used to semi-automate validation and interoperation processes. © 2013 Wiley Periodicals, Inc. Complexity 19: 56–63, 2014

Modeling sustainability transitions on complex networks

Abstract: There has been renewed interest in sociotechnical systems in the context of transitioning to a more sustainable society. While gains have been made in the qualitative understanding of sustainable transitions and sociotechnical systems, these approaches have not been well-operationalized. Given the importance of meeting future energy and environmental policy targets, there is need to develop predictive techniques and more robust methods to quantify and analyze sociotechnical systems undergoing rapid change and uncertainty due to sustainability pressures. Sustainability transitions depend on large-scale diffusion of technological and behavioral innovations on physical and virtual networked systems. Transitions can therefore be viewed as a subclass of diffusion phenomenon and subject to a range of mathematical and computational methods. We review, categorize, and critically assess methodological and theoretical approaches that integrate different aspects of sustainability, innovation, and complexity. We argue that these approaches should be adapted to improve our understanding of the behavior and dynamics of a broad range of sociotechnical systems to meet sustainability objectives. We therefore also make the conceptual link between complexity and sustainability as complimentary fields of research to inform policy and decision making to achieve more sustainable outcomes. © 2014 Wiley Periodicals, Inc. Complexity 19: 8-22, 2014

Characterizing conversion points and complex infrastructure systems: Creating a system representation for agent-based modeling

Abstract: 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

Scale-free power-laws as interaction between progress and diffusion

Abstract: While scale-free power-laws are frequently found in social and technological systems, their authenticity, origin, and gained insights are often questioned, and rightfully so The article presents a newly found rank-frequency power-law that aligns the top-500 supercomputers according to their performance Pursuing a cautious approach in a systematic way, we check for authenticity, evaluate several potential generative mechanisms, and ask the "so what" question We evaluate and finally reject the applicability of well-known potential generative mechanisms such as preferential attachment, self-organized criticality, optimization, and random observation Instead, the microdata suggest that an inverse relationship between exponential technological progress and exponential technology diffusion through social networks results in the identified fat-tail distribution This newly identified generative mechanism suggests that the supply and demand of technology "technology push" and "demand pull" align in exponential synchronicity, providing predictive insights into the evolution of highly uncertain technology markets © 2013 Wiley Periodicals, Inc Complexity 19: 56-65, 2014

Systemic view of learning scientific concepts: A description in terms of directed graph model

Abstract: This study suggests a systemic view on concept learning, in which concepts are seen as complex, dynamically evolving structures with robust and persistent patterns emerging from loosely connected elemental pieces. The model is represented in the form of a directed graph, and it explains many empirically identified features of learning paths, including: (1) the stability of learned concepts, (2) changes in concept attributions (ontological shift) as guided by theoretical knowledge, and (3) the evolution of concepts as driven by model competition with the accumulation of evidence. The results thus show applicability of the systemic view and the directed graph model. © 2013 Wiley Periodicals, Inc. Complexity 19: 27–37, 2014

Which forces reduce entropy production

Abstract: A real pendulum with friction will oscillate for a while after a short push, but will eventually come to rest close to a location where is potential energy has a minimum. If the system is closed, i.e. without a source of energy, it will eventually stop moving at a location near a minimum of the potential, no matter what type of friction force acts on the pendulum. This ‘variation principle’ is a simple concept to predict the long term behavior of mechanical systems, even if the details of the friction forces are unknown.

Dynamical analysis of a delayed singular prey-predator economic model with stochastic fluctuations

Abstract: This article studies a delayed singular prey-predator economic model with stochastic fluctuations, which is described by differential-algebraic equations due to a economic theory. Local stability and Hopf bifurcation condition are described on the delayed singular prey-predator economic model within deterministic environment. It reveals the sensitivity of the model dynamics on gestation time delay. A phenomenon of Hopf bifurcation occurs as the gestation time delay increases through a certain threshold. Subsequently, a singular stochastic prey-predator economic model with time delay is obtained by introducing Gaussian white noise terms to the above deterministic model system. The fluctuation intensity of population and harvest effort are calculated by Fourier transforms method. Numerical simulations are carried out to substantiate these theory analysis. © 2013 Wiley Periodicals, Inc. Complexity 19: 23-29, 2014

Sketching a network portrait of the humber region

Abstract: 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

An exploration of social identity: The structure of the BBC news-sharing community on Twitter

Abstract: Online social media influence the flow of news and other information, potentially altering collective social action while generating a large volume of data useful to researchers. Mapping these networks may make it possible to predict the course of social and political movements, technology adoption, and economic behavior. Here, we map the network formed by Twitter users sharing British Broadcasting Corporation BBC articles. The global audience of the BBC is primarily organized by language with the largest linguistic groups receiving news in English, Spanish, Russian, and Arabic. Members of the network primarily "follow" members sharing articles in the same language, and these audiences are primarily located in geographical regions where the languages are native. The one exception to this rule is a cluster interested in Middle East news which includes both Arabic and English speakers. We further analyze English-speaking users, which differentiate themselves into four clusters: one interested in sports, two interested in United Kingdom UK news-with word usage suggesting this reflects political polarization into Conservative and Labour party leanings-and a fourth group that is the English speaking part of the group interested in Middle East news. Unlike the previously studied New York Times news sharing network the largest scale structure of the BBC network does not include a densely connected group of globally interested and globally distributed users. The political polarization is similar to what was found for liberal and conservative groups in the New York Times study. The observation of a primary organization of the BBC audience around languages is consistent with the BBC's unique role in history as an alternative source of local news in regions outside the UK where high quality uncensored news was not available. © 2014 Wiley Periodicals, Inc. Complexity 19: 55-63, 2014

Scaling in structural complexity

Abstract: Structural complexity has been shown to be a measure of the variety of load paths in structures with high degree of static indeterminacy, for example, frames. The variations of the value of complexity parameters across different structures have been investigated in previous researches. Herein, the effects of scaling on load distribution and on geometry of the structural scheme are outlined. A scale invariance is shown for load magnitude. Complexity variation is outlined for geometric similar structures, depending essentially on the consistency of the load set. A transition in the behavior of the structural scheme under loads is recorded in case of similar structures from small to large scales. The results are discussed. © 2014 Wiley Periodicals, Inc. Complexity 20: 57-63, 2014

Data analysis using circular causality in networks

Abstract: Complex systems in causal relationships are known to be circular rather than linear; this means that a particular result is not produced by a single cause, but rather that both positive and negative feedback processes are involved. However, although interpreting systemic interrelationships requires a language formed by circles, this has only been developed at the diagram level, and not from an axiomatic point of view. The first difficulty encountered when analysing any complex system is that usually the only data available relate to the various variables, so the first objective was to transform these data into cause-and-effect relationships. Once this initial step was taken, our discrete chaos theory could be applied by finding the causal circles that will form part of the system attractor and allow their behavior to be interpreted. As an application of the technique presented, we analyzed the system associated with the transcription factors of inflammatory diseases. © 2013 Wiley Periodicals, Inc. Complexity 19: 15-19, 2014