Bijayalaxmi Panda, Soumya Sahoo, Sovan Kumar Patnaik Abstract— Cluster analysis is one of the major techniques in pattern recognition, which is basically considered as one of the unsupervised learning technique. We can apply clustering techniques in various areas like clustering medicine, business, engineering systems and image processing, etc.,The traditional hard clustering methods restrict t...

Determination of the fuzzy membership functions in a given fuzzy logic system is the key factor for resulting in the best performance. Thus, in this study, particle swarm optimization (PSO) and artificial bee colony (ABC), relatively new member of swarm intelligence, are used to adjust the shape of fuzzy membership functions, respectively. Proposed methods have been implemented and compared for...

In this article the hybrid optimization algorithm of differential evolution and particle swarm is introduced for designing the fuzzy rule base of a fuzzy controller. For a specific number of rules, a hybrid algorithm for optimizing all open parameters was used to reach maximum accuracy in training. The considered hybrid computational approach includes: opposition-based differential evolution al...

In the past two decades, many forecasting models based on the concepts of fuzzy time series have been proposed for dealing with various problem domains. In this paper, we present a novel model to forecast enrollments and the close prices of stock based on particle swarm optimization and generalized fuzzy logical relationships. After that some concepts of the generalized fuzzy logical relationsh...

Image segmentation is one of the key techniques in the field of image understanding and computer vision. To determine the optimal threshold in image segmentation, an effective image threshold segmentation method based on fuzzy logic is presented. A new kind of fuzzy entropy is defined, that is not only related to the membership, but also related to probability distribution. According to the max...

This paper presents a new improved from particle swarm optimization to tune optimal rule-base of a Fuzzy Proportional Integral Differential (FPID) which leads to damp low frequency oscillation following disturbances in power systems, while called Particle Swarm Optimization with Time Variant Acceleration Coefficient (PSO-TVAC). Thus, extraction of an appropriate set of rules or selection of an ...

Problem statement: The main objective of this research is to obtain the speed control of switched reluctance motor with minimum settling time and without overshoot. Approach: A new algorithm has been developed with the combination of differential evolution and particle swarm optimization and applied for speed control of switched reluctance motor under sudden change in speed. Also speed control ...

The fuzzy particle swarm optimization (FPSO-RRB- algorithm is used to solve the logistics transportation time problem, a three-dimensional coding method based on receiving point, position sequence and rounding operation proposed, results are compared with those of algorithm. experimental show that can effectively optimize time.

in the past few decades, increasing growth of wind power plants causes different problems for the power quality in the grid. normal and transient impacts of these units on the power grid clearly indicate the need to improve the quality of the electricity generated by them in the design of such systems. improving the efficiency of the large-scale wind system is dependent on the control parameter...