Following the successful applications of the fuzzy models in various application domains, the issue of automatic generation of Fuzzy Rule Based Systems (FRBSs) from observational data was widely studied in the literature and several approaches have been proposed. Most approaches were designed to search for the best accuracy of the generated model, neglecting the interpretability of FRBSs, which...

In recent years, soft computing methods have generated a large research interest. The synthesis of the fuzzy logic and the evolutionary algorithms is one of these methods. A particular evolutionary algorithm (EA) is differential evolution (DE). As for any EA, DE algorithm also requires parameters tuning to achieve desirable performance. In this paper tuning the perturbation factor vector of DE ...

The identification of a model is one of the key issues in the field of fuzzy system modeling and function approximation theory. An important characteristic that distinguishes fuzzy systems from other techniques in this area is their transparency and interpretability. Especially in the construction of a fuzzy system from a set of given training examples, little attention has been paid to the ana...

Hybridization of intelligent systems is a promising research field of modern computational intelligence concerned with the development of the next generation of intelligent systems. A fundamental stimulus to the investigations of hybrid intelligent systems is the awareness in the academic communities that combined approaches might be necessary if the remaining tough problems in artificial intel...

Fraud is causing huge losses to our financial world. This work describes the use of a committee decision system using genetic programming to evolve fuzzy logic rules capable of detecting suspicious home insurance claims. Details of the evolutionary-fuzzy system, the committee decision maker and the data preprocessing are provided. Finally, a series of experiments are described, showing that the...

based on the problems caused by today conventional vehicles, much attention has been put on the fuel cell vehicles researches. however, using a fuel cell system is not adequate alone in transportation applications, because the load power profile includes transient that is not compatible with the fuel cell dynamic. to resolve this problem, hybridization of the fuel cell and energy storage device...

This paper proposes a nonlinear approach for designing traffic responsive and coordinated ramp control using a self adapting fuzzy system. The traffic responsive metering rate is determined every minute by an adaptive fuzzy logic algorithm. The coordination between multiple on-ramps is ensured by the integration of a common input into all ramp controllers upstream of a bottleneck and a periodic...

This paper presents a new evolutionary fuzzy logic system for use in the assembly of optical bre components. The system optimizes the light output from a bre by applying a gradientbased algorithm enhanced with momentum information. The parameters of the algorithm are adjusted on-line by a fuzzy controller according to the progress of the alignment process. The control knowledge base is automati...

System identification is the task to map several related components of a real world system into a model. If this is done by transferring human expertise into a model, the process is called knowledge-driven modeling. If the system information is embedded in data-bases and the implicit existent expertise is mapped by algorithms into a model, the process is called data-driven modeling. This thesis...

In this paper, we present an evolutionary multiobjective learning model achieving cooperation between the rule base and the adaptive fuzzy operators of the inference system in order to obtain simpler, more compact and still accurate linguistic fuzzy models by learning fuzzy inference adaptive operators together with rules. The multiobjective evolutionary algorithm proposed generates a set of fu...