Particle Swarm Optimization algorithm (PSO) is a popular stochastic searching optimization algorithm to solve complicated optimization problems. The approach of retrieving duct parameters from the sea-surface reflected radar clutter is also known as Refractivity From Clutter (RFC) technique. RFC technique provides the near-real-time duct parameters to evaluate the radio system performance, with...

Abstract: Constraint handling is one of the most difficult parts encountered in practical engineering design optimizations. Different kinds of methods were proposed for handling constraints namely, genetic algorithm, self-adaptive penalty approach and other evolutionary algorithms. Particle Swarm Optimization (PSO) efficiently solved most nonlinear optimization problems with inequity constraint...

In recent years, genetic algorithms (GA) and particle swarm optimization (PSO) techniques have attracted considerable attention among various modern heuristic optimization techniques. In this paper PSO is employed for finding stable reduced order models of large-scale linear Interval systems. In this algorithm the numerator and denominator polynomials are determined by minimizing the Integral s...

A new hybrid algorithm of Particle Swarm Optimization and Genetic Algorithm (PSOGA) is presented to get the optimum design of truss structures with discrete design variables. The objective function chosen in this paper is the total weight of the truss structure, which depends on upper and lower bounds in the form of stress and displacement limits. The Particle Swarm Optimization basically model...

Aiming to the problems of slow convergence speed and being easily early-maturing etc. in existing network based on standard particle swarm algorithm, this paper proposes a wireless sensor network coverage optimization algorithm based on the genetic particle swarm optimization (PSO). The wireless sensor maximum coverage is regarded as the objective function, the genetic algorithm with adaptive c...

: Circuit partitioning is the more critical step in the physical design of various circuit in VLSI. In this partitioning main objective is to minimize the number of cuts. For this PSO algorithm is proposed for the optimization of VLSI inter connection (net list) bipartition. Meanwhile, the corresponding evaluation function and the operators of crossover and mutation are designed. The algorithm ...

Particle Swarm Optimization (PSO) is a swarm intelligence search method based on the behavior of birds flocking and fish schooling. It is known for its ability to perform fast computation compared to other evolutionary computational methods like Genetic Algorithms. Several parameter control methods have been developed to make the PSO algorithm faster and more accurate such as linearly decreasin...

In this paper, well-known PSO algorithms reported in the literature for solving continuous function optimization problems were comparatively evaluated by considering real world data clustering problems. Data clustering problems are solved, by considering three performance clustering metrics such as TRace Within criteria (TRW), Variance Ratio Criteria (VRC) and Marriott Criteria (MC). The result...

in this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. the new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-pso and the shuffled sub-swarms particle optimization (sspso) technique. it is known that the θ-pso algorithm has better optimization performance than standard pso al...

This paper presents a Hybrid Genetic Algorithm (HGA) Particle Swarm Optimization (PSO) approach to solve Economic Emission Optimal Power Flow problem. The proposed approach optimizes two conflicting objective functions namely, fuel cost minimization and emission level minimization of polluted gases namely NOX, SOX and COx simultaneously while satisfying operational constraints. An improved PSO ...