The control of nonlinear chaotic system and the estimation of parameters is a vital issue in nonlinear science. Studies on parameter estimation for chaotic systems have been investigated recently. A variant of Particle Swarm Optimization (PSO) known as Chaotic Multi Swarm Particle Swarm Optimization (CMS-PSO) is proposed which is inspired from the metaphor of ecological co-habitation of species...

This paper studies wireless sensor networks node deployment problem and proposes intelligent single particle optimizer based wireless sensor networks adaptive coverage. According to the probability model measure characteristic of wireless sensor nodes, the method adaptively determines the optimal deployment of sensor nodes using intelligent single particle optimizer, achieving sensor node based...

in this paper, a new enhanced version of the particle swarm optimization (pso) is presented. an important modification is made by adding probabilistic functions into pso, and it is named probabilistic particle swarm optimization (ppso). since the variation of the velocity of particles in pso constitutes its search engine, it should provide two phases of optimization process which are: explorati...

in this paper, the unified power flow controller (upfc) is enhanced with a chaotic particle swarm optimization (cpso) damping controller in order to mitigate the low frequency oscillations (lfo) in a single machine infinite bus (smib) power system. the designed damping controller is an optimized lead-lag controller, which extracts the speed deviation of the generator rotor and generates the out...

Abstract: This study proposes a novel chaotic quantum-behaved particle swarm optimization (CQPSO) algorithm for solving shortterm hydrothermal scheduling problem with a set of equality and inequality constraints. In the proposed method, chaotic local search technique is employed to enhance the local search capability and convergence rate of the algorithm. In addition, a novel constraint handlin...

numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...

Data clustering is a powerful technique for discerning the structure of and simplifying the complexity of large scale data. An improved technique combining chaotic map particle swarm optimization (CPSO) with an acceleration strategy, is proposed in this paper. Accelerated chaotic particle swarm optimization (ACPSO) searches for cluster centers of an arbitrary data set and can effectively find t...

Particle swarm optimization algorithm is easy to reach premature convergence in the solution process, and fall into the local optimal solution. Aiming at the problem, this paper proposes a particle swarm optimization algorithm with chaotic mapping (CM-PSO). The algorithms uses chaotic mapping function to optimize the initial state of population, improve the probability of obtain optimal solutio...

In this article, multiple-product PVRP with pickup and delivery that is used widely in goods distribution or other service companies, especially by railways, was introduced. A mathematical formulation was provided for this problem. Each product had a set of vehicles which could carry the product and pickup and delivery could simultaneously occur. To solve the problem, two meta-heuristic methods...

Clustering is a popular data analysis and data mining technique. In this paper, a novel chaotic particle swarm fuzzy clustering (CPSFC) algorithm based on chaotic particle swarm (CPSO) and gradient method is proposed. Fuzzy clustering model optimization is challenging, in order to solve this problem, adaptive inertia weight factor (AIWF) and iterative chaotic map with infinite collapses (ICMIC)...