Traffic information collection and traffic flow control around the crossroads are main topics of current traffic related research. The most commonly used method of traffic signal control at present is fixed-time control which only applies to small traffic flow circumstances with low efficiency. Therefore, we propose a new method which is an adaptive crossroads control model based on Wireless Se...

Agent-based Methodology (ABM) is becoming indispensable for the inter-disciplinary study of social and economic complex adaptive systems. The essence of ABM lies in the notion of autonomous agents whose behavior may evolve endogenously and can generate and mimic the corresponding complex system dynamics that the ABM is studying. Over the past decade, many computational intelligence (CI) methods...

Inequalities in the social determinants of health (SDH), which drive avoidable health disparities between different individuals or groups, is a major concern for a number of international organisations, including the World Health Organization (WHO). Despite this, the pathways to changing inequalities in the SDH remain elusive. The methodologies and concepts within system science are now viewed ...

Static Synchronous Series Compensator (SSSC) is a series compensating Flexible AC Transmission System (FACTS) controller for maintaining to the power flow control on a transmission line by injecting a voltage in quadrature with the line current and in series mode with the line. In this work, an Adaptive Network-based Fuzzy Inference System controller (ANFISC) has been proposed for controlling o...

Cities are changing constantly. All urban systems face different conditions from day to day. Even when averaged regularities can be found, urban systems will be more efficient if they can adapt to changes at the same speeds at which these occur. Technology can assist humans in achieving this adaptation. Inspired by cybernetics, we propose a description of cities as adaptive systems. We identify...

Dynamically Adaptive Systems (DASs) adjust their behaviour at runtime to tolerate changes in context. With potentially incomplete or inaccurate knowledge of an operating environment, tailoring specific behavioural adjustments to individual contextual changes is a time-consuming and errorprone process. i* models of a DAS' behavioural adjustments can aid understanding, and can form part of the sp...

The purpose of the present paper is to analyze how the predictive distribution estimated using a set of context dependent nonlinear adaptive predictors can be used to localize edges in graylevel images. Since the adaptive predictors have the potential of learning repetitive structure, as those characteristic to certain textures, our predictive edge detection scheme may be a practical way to con...

Complex adaptive systems consist of a multitude of agents from whose individual adaptation efforts the adaptive behavior of the system as a whole emerges. In this paper it will be argued that capitalism is a complex adaptive system. Except for its particular mode of production many of its features are typical for such a system. A case in point is the way in which economic growth emerges as a co...

We live in a very complex world where we face complex phenomena such as social norms and new technologies. To deal with such phenomena, social scientists often use reductionism approach where they reduce them to some lower-lever variables and model the relationships among them through a scheme of equations. This approach that is called equation based modeling (EBM) has some basic weaknesses in ...