voltage profile and losses are important factors in a distribution network in which there arevariety of ways to improve them. in this paper, distributed generation (dg) is used as a solutionto improve the above characteristics. backward/forward sweep load flow algorithm is used dueto the inefficiency of usual load flow algorithms because of high r/x ratio and their lack ofconvergence in distrib...

In view of the shortcomings of the test data generation algorithm including particle swarm optimization algorithm and ant colony algorithm, a new algorithm is proposed, which is based on the combination of particle swarm algorithm and parameter adjustment. This algorithm can dynamically adjust its search capabilities based on the fitness value of particles , combine the advantages of particle s...

Niching as an important technique for multimodal optimization has been used widely in the Evolutionary Computation research community. This chapter aims to provide a survey of some recent efforts in developing stateof-the-art PSO niching algorithms. The chapter first discusses some common issues and difficulties faced when using niching methods, then describe several existing PSO niching algori...

The problem of finding appropriate representations for various is a subject of continued research in the field of artificial intelligence and related fields. In some practical situations, mathematical and computational tools for faithfully modeling or representing systems with uncertainties, inaccuracies or variability in computation should be provided; and it is preferable to develop models th...

Clustering is a method which divides data objects into groups based on the information found in data that describes the objects and relationships among them. There are a variety of algorithms have been developed in recent years for solving problems of data clustering. Data clustering algorithms can be either hierarchical or partitioned. Most promising among them are K-means algorithm which is p...

This paper presents a comparison between the use of particle swarm optimization and the use of genetic algorithms for tuning the parameters of a novel fuzzy classifier. In the previous work on the classifier, the large amount of time needed by genetic algorithms has been significantly diminished by using an optimized initial population. Even with this improvement, the time spent on tuning the p...

This paper presents a particle swarm ant colony optimization for design of truss structures. The algorithm is based on the particle swarm optimizer with passive congregation and ant colony optimization. The particle swarm ant colony optimization applies the particle swarm optimizer with passive congregation for global optimization and ant colony approach is employed to update positions of parti...

This paper introduces an enhancement to the particle swarm optimization algorithms that models a characteristic of social groups: the disagreements between individuals. After a short introduction, we describe the new concept theoretically and define a special type of particle swarm optimization with disagreements: the 6σ-PSOD. Based on it, we conduct some tests proving that it can perform bette...

This chapter presents particle swarm optimization (PSO) based algorithms. After an overview of PSO’s development and application history also two application examples are given in the following. PSO’s robustness and its simple applicability without the need for cumbersome derivative calculations make it an attractive optimization method. Such features also allow this algorithm to be adjusted fo...