Particle swarm optimization (PSO) algorithm is a kind of random optimization algorithm based on swarm intelligence. Swarm intelligence of PSO is produced by cooperation and competition between particles, which is used for guiding optimization search. PSO has been studied widely in many applications due to its good global searching ability. Currently PSO has been widely used in function optimiza...

Due to many classical identification methods cannot be directly used for closed-loop control system, an improved identification method is proposed to simultaneously identify model parameters and the structure. The improved identification method used the genetic algorithm to estimate the initial search scope for the PSO algorithm, and then used the search result as the initial value of the Rosen...

Vigenere cipher is a polyalphabetic substitution cipher with a very large key space. In this paper we have investigated the use of PSO for the cryptanalysis of vigenere cipher and proposed PSO with Markov chain random walk in which some of the worst particles are replaced with new better random particles to enhance the efficiency of PSO algorithm. Based on our experimental results, it is shown ...

Because of computational drawbacks of conventional numerical methods in solving complex optimization problems, researchers may have to rely on meta-heuristic algorithms. Particle swarm optimization (PSO) is one of the most widely used algorithms due to its simplicity of implementation and fast convergence speed. Also, the cuckoo search algorithm is a recently developed meta-heuristic optimizati...

This paper proposes a new parameter identification approach for a single-phase induction motor (SPIM) whose parameters are usually obtained using several traditional techniques such as the DC, no-load, load and locked-rotor tests. It can be realized that the traditional techniques are complicated and require a higher cost with extra equipment. The proposal is based on using a Gauss particle swa...

This paper introduces the Particle Swarm Optimization (PSO) algorithm to solve the optimal network reconfiguration problem for power loss reduction. The PSO is a relatively new and powerful intelligence evolution method for solving optimization problems. It is a population-based approach. The PSO was inspired from natural behavior of the bees on how they find the location of most flowers. The p...

The parts optimization are very important for scroll compressor design. According to existing problems of current optimization algorithm and actual optimization problems, the improved optimization algorithm—genetic-particle swarm optimization (GA-PSO) is proposed for scroll plate optimization. The optimization method integrates crossover of genetic algorithm (GA) and evolutionary mechanism of p...

The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous best to optimize problems. One problem exists in PSO is its tendency of trapping into local optima. In this paper, a fast particle swarm optimization (FPSO) algorithm is proposed by combining PSO and the Cauchy mutation...

There is a concept of PSO algorithm which is very much efficient and effective with optimized result popular these days in so many streams. This paper provides the run of PSO on cloudSim with comparison analysis from different simulators. The paper covers five different sections in details. First is introduction towards the topic. Then cloud computing with cloudSim comes as another section whic...

In classification, feature selection is an important, but difficult problem. Particle swarm optimisation (PSO) is an efficient evolutionary computation technique. However, the traditional personal best and global best updating mechanism in PSO limits its performance for feature selection and the potential of PSO for feature selection has not been fully investigated. This paper proposes a new in...