In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large dataset. While generating frequent item sets from a large dataset using association rule mining, computer takes too much time. This can be improved by using particle swarm optimization algorithm (PSO). PSO algorithm is population based heuristic search technique used for s...

This paper proposes a hybrid cooperative quantum particle swarm optimization (HCQPSO), hybridizing dynamic varying search area, cooperative evolution, simulated annealing and quantum particle swarm optimization (PSO) for function optimization. In the proposed HQCPSO, a technique of dynamic varying search area helps reduce the search spaces and populations of swarms, which could make the optimiz...

In this paper, an efficient optimization algorithm is proposed based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to optimize truss structures. The proposed algorithm utilizes the PSO for finding high fitness regions in the search space and the SA is used to perform further investigation in these regions. This strategy helps to use of information obtained by swarm in an opt...

Particle Swarm Optimization (PSO) is a population based heuristic search method for finding global optimal values in multi-disciplinary design optimization problems. PSO is based on simple social behavior exhibited by birds and insects. Due to its simplicity in implementation, PSO has been increasingly gaining popularity in the optimization community. Previous work by the authors demonstrated s...

يا هچروم يدنب هشوخ متيروگلا ياراد پ ا ار يددعتم ياهرتم هلمج زا ،نتشادرب هب طوبرم ياهرتماراپ نتشاذگ اه هداد ديد عاعش ، يم هك دشاب ريثات و دنراد متيروگلا ييارگمه و دركلمع رد يدايز اطخ و شيامزآ تروص هب لاومعم نييعت يم رگ د دن . شور هلاقم نيا رد ي رب ينتبم CLA-PSO 1 ي هتسسگ لدم كي هك PSO دشاب يم يارب قيبطت كيتاموتا پ ياهرتمارا يا هچروم يدنب هشوخ يم داهنشيپ ددرگ . روظنم هب گلا ساسا رب هك د...

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search techniqu...

In this paper, a new segmentation method for images based on particle swarm optimization (PSO) is proposed. The new method is produced through combining PSO algorithm with one of region-based image segmentation methods, which is named Seeded Region Growing (SRG).The algorithm of SRG method performs a segmentation of an image with respect to a set of points known as seeds. Two problems are relat...

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the chaotic systems theory, this paper proposed a novel chaotic PSO combined with an implicit filtering (IF) local search method to solve economic dispatch problems. Since chaotic mapping enjo...

Feature selection is an optimization problem in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable recognition accuracy. Feature selection is of great importance in pattern classification, medical data processing, machine learning, and data mining applications. In this paper, continuous particle swarm optimization (PSO...

This paper presents particle swarm optimization (PSO) method to find the prime factors of a composite number. Integer factorization is a well known NP hard problem and security of many cryptosystem is based on difficulty of integer factorization. A particle swarm optimization algorithm for integer factorization has been devised and tested on different 100 numbers. It has been found that the PSO...