This paper proposes a hybrid Particle Swarm Optimization (PSO) method, which is based on the fusion of the PSO, Clonal Selection Algorithm (CSA), and Mind Evolutionary Computation (MEC). The clone function borrowed from the CSA and MEC-characterized similartaxis and dissimilation operations are embedded in the original PSO algorithm. Simulations of nonlinear function optimization are made to co...

In order to improve the performance of PSO algorithm, number of its variants has been made. This paper presents detail overview of the basic concepts of PSO and its variants. Many variants of PSO have been developed due to improved speed of convergence and quality of solution found by Researchers. The Applications of PSO in Complex Environments is discussed. Modifications, both those already de...

Particle swarm optimization (PSO) is a newer evolutionary computational method than genetic algorithm and evolutionary programming. PSO has some common properties of evolutionary computation like randomly searching, iteration time and so on. However, there are no crossover and mutation operators in the classical PSO. PSO simulates the social behavior of birds: Individual birds exchange informat...

This paper proposes a novel application of a chaos particle swarm optimization (PSO) algorithm for tracking a maximum power point (MPP) of a solar photovoltaic (PV) panel under varying atmospheric conditions. Solar PV cells have a nonlinear V-I characteristic with a distinct MPP which depends on environmental factors such as temperature and irradiation. In order to continuously harvest maximum ...

Particle swarmoptimization (PSO) is a heuristic global optimizationmethod, proposed originally byKennedy and Eberhart in 1995. It is now one of themost commonly used optimization techniques.This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO)...

This study proposes a multi-objective optimization model of two cascade reservoirs in the Upper Yellow River basin for increasing social well-beings in general while simultaneously mitigating ice/flood threats. We first develop a strategy of dimensionality reduction and constraint transformation to largely diminish the complexity of the optimization system and next propose a novel search method...

Psoralen (PSO), the active ingredient of Fructus Psoraleae (FP) the dried ripe fruit of Psoralea corylifolia L., has been commonly used in traditional Chinese medicine (TCM) for the treatment of osteoarthritis (OA). We found that PSO activates cartilaginous cellular functions of rat chondrocytes in vitro. However, the effect of PSO on chondrocyte proliferation and the precise mechanisms involve...

We propose an inter-disciplinary approach to particle swarm optimization (PSO) by establishing a molecular dynamics (MD) formulation of the algorithm, leading to a physical theory for the swarm environment. The physical theory provides new insights on the operational mechanism of the PSO method. In particular, a thermodynamic analysis, which is based on the MD formulation, is introduced to prov...

This article presents a new technique to detect a premature atrial contraction (PAC). The technique employs a hybrid of particle swarm optimization (PSO) and fuzzy inference system (FIS), and is called PSO-FIS. In the detection electrocardiographic features are used for the inputs of PSO-FIS. In PSO-FIS, a PSO is used to find the optimal parameters of the FIS. A Gaussian function is employed fo...

In this paper, a novel Particle Swarm Optimization (PSO) identification algorithm for time-varying systems with a colored noise is presented. Presented criterion function can show not only outside system output error but also inside parameters error in order to explain more difference between actual and estimative system. Identification algorithm may consist of many different PSO algorithms tha...