Particle swarm optimization algorithm in solving complex functions, such as slow convergence, accuracy is not high, easily falling into local optimum problem. Based on the chaos optimization is introduced into particle swarm optimization algorithm, given the chaotic particle swarm optimization algorithm. In order to improve the image quality of CMOS image sensor, the image of the main noise sou...

In this paper, an improved hybrid algorithm combining particle swarm optimization (PSO) with backpropagation algorithm (BP) is proposed to train feedforward neural networks (FNN). PSO is a global search algorithm, but the swarm in PSO is easy to lose its diversity, which results in premature convergence. On the other hand, BP algorithm is a gradient-descent-based method which has good local sea...

in this article, a multi-objective memetic algorithm (ma) for rule learning is proposed. prediction accuracy and interpretation are two measures that conflict with each other. in this approach, we consider accuracy and interpretation of rules sets. additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. this...

In this paper a narrative approach for designing FIR low pass filter is presented by practicing hybrid technique of Swine Influenza Model based Optimization (SIMBO) and Genetic Algorithm (GA). Premature convergence was the major difficulty faced by SIMBO algorithm individually in FIR filter design. To address this problem, a hybrid SIMBO-GA is proposed in this paper. GA is used to help SIMBO es...

The purpose of this paper is to describe and evaluate a new algorithm for optimization. The new algorithm is named the Genetic Flock Algorithm. This algorithm is a type of hybrid of a Genetic Algorithm and a Particle Swarm Optimization Algorithm. The paper discusses strengths and weaknesses of these two algorithms. It then explains how the Genetic Flock Algorithm combines features of both and g...

Service identification step is a basic requirement for a detailed design and implementation of services in a Service Oriented Architecture (SOA). Existing methods for service identification ignore the automation capability while providing human based prescriptive guidelines, which mostly are not applicable at enterprise scales. In this paper, we propose a top down approach to identify automatic...

Suitable solutions for multi-objective optimization problems are investigated as a set of solutions in the literature, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. The proposed algorithm in this paper is a hybrid of the particle swarm optimization algorithm [1] and a random search technique with quadratic approximation formula[2] n...