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The soft electrical properties are limiting Proton Exchange Membrane Fuel Cell (PEMFC) to be directly applied. To overcome such shortcoming, the high efficiency structure Four Switch Buck-Boost (FSBB) converter, which combines with Fractional Order PID (FOPID) controller, is used as pre-stage power converter of PEMFC to achieve regulated output. Also, Particle Swarm Optimization (PSO) based on the...
Particle Swarm Optimization (PSO) is an evolution-nary computation technique. Separate adjustment to inertia weight and learning factors in PSO undermines the integrity and intelligent characteristic in the evolutionary process of particle swarm to some extent, thus it is not suitable for solving most complicated optimization problems. On the basis of previous researches, the aim of this study was...
In view of the particle swarm optimization (PSO) algorithm's shortages of easily trapping into local optimum and premature convergence, an improvement research from the perspective of interaction mechanism among particles is made in this paper. Consider advantages and disadvantages of the current improved PSO algorithms from the aspect of force, the two-stage force particle swarm optimization (TFPSO)...
This paper presents a comparison of Bat and Particle Swarm Optimization (PSO) algorithms for optimization of lathe tool positional error in a developed machine vision system for determination of lathe tool position and verification. Bat algorithm is based on echolocation behavior of bats while PSO is inspired by social behavior of birds flocking in search for food. Both metaheuristic algorithms were...
The development of body Area Network and wireless sensor system had made drastic changes in the healthcare concept of human life. It is very usefull for elder people those who are being the burden of modern society. The elderly health care system gives continuous monitoring of the old person and give instant diagnosis result or medical assistance to the people. The system mainly considered with three...
With the development of intelligent algorithm, GA and PSO have become the hot spot for the study on multi-objective optimization in recently years. Information sharing is the core of PSO algorithm, Comparing with GA, PSO algorithm has less variables to adjust and is easy to achieve, so it is widely used in engineering. This paper focus on the comparation on several PSO algorithm and introduce a kind...
Any Web site may have the continuous improvement based on the getting information of the users' needs. There is a step to achieve it by the collection of users' search data and analysis of those data. The swarm intelligence technique of Particle Swarm Optimization(PSO) is applied for evolving similar user groups. PSO is important to identify the web users' travels with the same interests. The data...
Infinite impulse response (IIR) adaptive filters have been developed to identify IIIR systems, but system identification is challenging due to non-unimodality of the error surface and the non-linear relationship between the error signal and the system parameters. Cat Swarm Optimization (CSO) was recently introduced to solve optimization problems with a new learning rule to achieve better performance...
Considering the characteristics of the nonlinear, complexity and relativity of the sintering burden system, the prediction model of sintering burden is established by BP neural network. In addition, a new optimization method of the sintering experiment is proposed, based on information entropy and chaotic improved particle swarm algorithm. The initial particle colony is produced by information entropy...
By making use of the advantages of Cuckoo Search (CS) algorithm and Particle Swarm Optimization (PSO), a hybrid optimization algorithm of PSO and CS was proposed. By CS-PSO, the search area of PSO was extended, and the defect of PSO is easily fall into point of local extremum that was improved. The simulation experiment results show that CS-PSO hybrid algorithm is better.
An enhanced particle swarm optimization algorithm (PSO) is presented in this paper to solve the optimal planning of multiple distributed generation sources (DG) in distribution networks. This problem can be divided into two sub-problems: The DG optimal size and location that would minimize the network real power losses. The proposed approach addresses the optimal size and location problems simultaneously...
Different techniques for the optimization of utility systems have been developed in recent decades. The objective of this paper is to introduce a new mathematical programming model applied to the operational optimization for the utility system. Particle Swarm Optimization (PSO) presented by Kennedy has been described for solving mixed integer linear programming (MILP). It is a simple algorithm that...
Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from premature convergence and high elapsed time when solving multimodal and large scale engineering problems. This problem becomes an evident drawback for embedded applications in which the microcontrollers often operates...
This paper focuses on traffic flow forecasting approach based on soft computing tools. The soft computing tools used is Particle Swarm Optimization (PSO) with Wavelet Network Model(WNM). The forecast of short-term traffic flow in timely and accurate is one of important contents of intelligent transportation system research. The modelling of traffic characteristics and the prediction of future traffic...
A new hybrid algorithm is introduced into solving job shop scheduling problems, which combines knowledge evolution algorithm(KEA) and particle swarm optimization(PSO) algorithm. By the mechanism of KEA, its global search ability is fully utilized for finding the global solution. By the operating characteristic of PSO, the local search ability is also made full use. Through the combination, better...
Present a image segmentation technique using fast fuzzy C Means clustering algorithm based on Particle Swarm Optimization Algorithm. This Algorithm utilizes the strong ability of the global optimizing of the PSO Algorithm, and avoids the sensitivity to local optimization of the Fast FCM algorithm. Furthermore, the PSO defines the centers and numbers of clustering automatically. Two algorithm combined...
Particle Swarm Optimization (PSO) modified to solve image processing problem with reference to enhancement technique is proposed in this paper. The enhancement process is an optimization problem with several constraints. The objective of the proposed PSO is to maximize an objective fitness criterion in order to improve the contrast and detail in an image by adapting the parameters of a novel extension...
An end-member extraction method for spectral unmixing that is based on Particle Swarm Optimization (PSO) is developed and presented in this paper. The objective function minimized by PSO is the volume of the simplex containing the hyperspectral vectors, following the geometrical characteristics inherent to the data sets. The proposed algorithm has been successfully applied to synthetic hyperspectral...
Production line, taking on the most production task, is the important part in manufacturing enterprise. Under determinate resource, the running state of the production line has a great impact on the production capacity. This paper, aiming the aero-engine casing production line, makes a systematic study on production line simulation, builds the model of aero-engine casing production line, and makes...
To solve the shortage of the application of conventional methods in beam broadening of phased array antennas, this paper has presented a method for beam broadening by constructing an initial phase based on particle swarm optimization (PSO) algorithm and genetic algorithms (GAs). The paper takes an S-band phased array antenna as an example to construct the same initial phase of linear distribution,...
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