In this paper, the ability of Immune Algorithm (IA) is investigated for VAr planning with the Static Var Compensator (SVC) in a large-scale power system. To enhance voltage stability, the planning problem is formulated as a multi-objective optimization problem for maximizing fuzzy performance indices. The multi-objective VAr planning problem is solved by the fuzzy IA and the results are compare...

This article develops an evolutional fuzzy particle swarm optimization (FPSO) learning algorithm to self extract the near optimum codebook of vector quantization (VQ) for carrying on image compression. The fuzzy particle swarm optimization vector quantization (FPSOVQ) learning schemes, combined advantages of the adaptive fuzzy inference method (FIM), the simple VQ concept and the efficient part...

detection & classification of power quality (pq) disturbances are the most important problems in distribution systems. in this paper, a new approach for the detection and classification of single and combined pq disturbances is proposed which utilizes fuzzy logic and particle swarm optimization (pso) algorithms. in this approach, first suitable features of the waveform of pq disturbances ar...

The need to deduce interesting and valuable information from large, complex, information-rich data sets is common to many research fields. Rule discovery or rule mining uses a set of IF-THEN rules to classify a class or category in a comprehensible way. Besides the classical approaches, many rule mining approaches use biologicallyinspired algorithms such as evolutionary algorithms and swarm int...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

0957-4174/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.eswa.2010.02.014 * Corresponding author. E-mail addresses: [email protected] (R. Roy), (S.P. Ghoshal). In this paper, various novel heuristic stochastic search techniques have been proposed for optimization of proportional–integral-derivative gains used in Sugeno fuzzy logic based automatic generation control of multi-area ther...

This paper is concerned with an optimization of GN (Granular Networks) based on PSO (Particle Swarm Optimization) and Information granulation). The GN is designed by the linguistic model using context-based fuzzy c-means clustering algorithm performing relationship between fuzzy sets defined in the input and output space. The contexts used in this paper are based on two-sided Gaussian membershi...

The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle ...