this paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (fpso) and fuzzy c-means (fcm) algorithms, to solve the fuzzyclustering problem, especially for large sizes. when the problem becomes large, thefcm algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. the pso algorithm does find ago...

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...

Data mining is being actively applied to stock market since 1980s. The various aspects of stock market to which data mining has been applied include predicting stock indices, predicting stock prices, portfolio management, portfolio risk management, trend detection, designing recommender systems etc. The various algorithms and methods which have been used for the same include neural networks, as...

In this paper, a new adaptive fuzzy reasoning method using compensatory fuzzy operators is proposed to make a fuzzy logic system more adaptive and more effective. Such a compensatory fuzzy logic system is proved to be a universal approximator. The compensatory neural fuzzy networks built by both control-oriented fuzzy neurons and decision-oriented fuzzy neurons cannot only adaptively adjust fuz...

This paper investigates the performance of fuzzy and Particle Swarm Optimization (PSO) based PID controllers for liquid level control of two tank non-interacting system. The main aim is to minimize system performance specifications, such as rise time, settling time, peak time and peak overshoot. Initially a fuzzy controller is applied and then to achieve further improvement in performance PSO i...