Modeling of complex dynamic systems, which are very complicated to establish mathematical models, requires new and modern methodologies that will exploit the existing expert knowledge, human experience and historical data. Fuzzy cognitive maps are very suitable, simple, and powerful tools for simulation and analysis of these kinds of dynamic systems. However, human experts are subjective and ca...

In this paper, we compare the inference capabilities of three different types of Fuzzy Cognitive Maps. A Fuzzy Cognitive Map is a Recurrent Artificial Neural Network that creates models as collections of concepts/neurons and the various causal relations that exist between these concepts/neurons. The three different types of Fuzzy Cognitive Maps that we study are the Binary, the Trivalent and th...

This paper presents Fuzzy Cognitive Maps as an approach in modeling the behavior and operation of complex systems. This technique is the fusion of the advances of the fuzzy logic and cognitive maps theories, they are fuzzy weighted directed graphs with feedback that create models that emulate the behavior of complex decision processes using fuzzy causal relations. There are some applications in...

Fuzzy Cognitive Map (FCM) is a soft computing modelling methodology for complex systems. Beyond the mathematical formulation of the FCM theory, there was a need of developing a software tool to facilitate the implementation of FCMs. This paper describes the use of a software tool that was developed to construct FCM models. Some theoretical elements of Fuzzy Cognitive Maps are presented. Then, i...

The necessity to use various tools – instructional media and technology for effective teaching using combined overlap block fuzzy cognitive maps (COBFCMS) defined by W.B. Vasantha Kandaswamy is analyzed in this paper. The combined overlap block FCM’s defined in this method become effective when the number of concepts can be grouped and are large in numbrs. In this paper we have analyzed the var...

This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the...

This paper investigates a hybrid methodology that combines fuzzy logic and neural networks, Fuzzy Cognitive Map (FCM), for modeling and controlling Supervisory Control Systems. A mathematical description of Fuzzy Cognitive Maps (FCM) will be presented and new construction methods will be extensively examined. A Fuzzy Cognitive Map will be developed to model and control a process example and the...

Rule Based Fuzzy Cognitive Maps (RBFCM) are proposed as an evolution of Fuzzy Causal Maps (FCM) that allow a more complete representation of cognition, since relations other than monotonic causality are made possible. Their structure is based on traditional fuzzy systems with feedback. The main problem to solve while trying to implement a RBFCM is the causal relation itself, since traditional f...

A technique for Fuzzy Cognitive Maps learning, which is based on the minimization of a properly defined objective function using the Particle Swarm Optimization algorithm, is presented. The workings of the technique are illustrated on an industrial process control problem. The obtained results support the claim that swarm intelligence algorithms can be a valuable tool for Fuzzy Cognitive Maps l...