A new hybrid technique for optimization of a multivariable function is proposed. This method is applied to the problem of complex time Green’s function of multilayer media. This technique combines Particle Swarm search algorithm with the gradient based quasi-Newton method. Superiority of the method is demonstrated by comparing its results with other optimization techniques.

To solve the problems of low precision, slow convergence speed and difficult data fusion of standard particle filtering algorithm, a new hybrid intelligent optimization algorithm applicable for data fusion is presented in this paper and will conduce to finding the ideal solution domain by making use of the global convergence of artificial fish swarm and enhancement of fusion precision by guidin...

This paper present the hybrid approaches of Particle Swarm Optimization (PSO) with Genetic Algorithm (GA). PSO and GA are population based heuristic search technique which can be used to solve the optimization problems modeled on the concept of Evolutionary Approach. In standard PSO, the non-oscillatory route can quickly cause a particle to stagnate and also it may prematurely converge on subop...

In order to further enhance the accuracy of Web information extraction, and overcome the shortcomings of the Hidden Markov Model (HMM) and its hybrid method in parameter optimization, a novel Web extraction algorithm based on a combined and improved particle swarm optimization, ant colony algorithm (IPSO-ACA) and HMM is presented. First, an HMM for information extraction is built. Second, an im...

Particle swarm optimization is affected by premature convergence, no guarantee in finding optimal solution, lack of solution amongst other issues. This paper reviews many literature on PSO and proposes a Hybrid MultiSearch Sub-Swarm PSO by using multiple sub swarm PSO in combination with multi search space algorithm. The particles are divided into equal parts and deployed into the number of sub...

This Paper represents a literature review of Swarm intelligence algorithm in the area of semi-supervised classification. There are many research papers for applying swarm intelligence algorithms in the area of machine learning. Some algorithms of SI are applied in the area of ML either solely or hybrid with other ML algorithms. SI algorithms are also used for tuning parameters of ML algorithm, ...

In light of the accuracy of particle swarm optimization-particle filter (PSO-PF) inadequate for multi-robot cooperative positioning, the paper presents population density particle swarm optimization-particle filter (PDPSO-PF), which draws cooperative coevolutionary algorithm in ecology into particle swarm optimization. By taking full account of the competitive relationship between the environme...

Evolutionary algorithms have proven to be robust tools in data processing for modeling dynamic, non-linear and complex processes due to their flexible mathematical structure to yield optimal results even with imprecise, ambiguity and noise at its input. The study is a soft-computing heuristic-based, hybrid approach that aims to provide computational intelligence via solving optimization task. T...

in this work, by using the particle swarm optimization the electron raman scattering for square double quantum wells is optimized. for this purpose, by combining the particle swarm algorithm together with the numerical solution procedures for equations, and also the perturbation theory we find the optimal structure that maximizes the electron raman scattering. application of this algorithm to t...

The construction site layout (CSL) design presents a particularly interesting area of study because of its relatively high level of attention to usability qualities, in addition to common engineering objectives such as cost and performance. However, it is difficult combinatorial optimization problem for engineers. Swarm intelligence (SI) was very popular and widely used in many complex optimiza...