... disturbance affects the system, the classic average weakening buffer operator is used to weaken its effects. Then, the new information accumulation parameters ? and the fractional-order cumulative generating operator parameter r, are optimized using the particle swarm optimization (PSO) technique. Findings...

... simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity...

...-19 period into stock price prediction. The goal of this study is to use an improved extreme learning machine (ELM), whose parameters are optimized by four meta-heuristics: harmony search (HS), social spider algorithm (SSA), artificial bee colony algorithm (ABCA) and particle swarm optimization (PSO...

... the efficiency of solving multi-objective flexible job shop scheduling problem (FJSP), an improved hybrid particle swarm optimization algorithm (IH-PSO) is proposed. Design/methodology/approach After reviewing literatures on FJSP, an IH-PSO algorithm for solving FJSP is developed. First, IH-PSO algorithm...

... researchers”) using particle swarm optimization (PSO) technique. Findings While exploitation was done using GA in the previous work, exploration is done in the current work based on PSO using the same grade score value to the objective function. Both the velocity and direction of high graded researchers...

..., particle swarm optimization (PSO), artificial bee colony (ABC) and method of musical composition (DMMC), for the districting problem. Design/methodology/approach In order to compare the performance of the proposed algorithms, they were tested on eight instances drawn from the Mexican electoral...

... method that is able to generate rules that work not only on numerical attributes but also on nominal ones. The key feature of this method, called learning vector quantization and particle swarm optimization (LVQ + PSO), is the finding of a reduced set of classifying rules. This is possible because...

... the scalable function performance tests about SAPSO, which aims to further evaluate the feasibility of the proposed SAPSO algorithm. Dr Zhou Cheng can be contacted at: zhou781105@163.com © Emerald Group Publishing Limited 2015 Particle swarm optimization BP neural network Combination...

... programming, grey simulation and particle swarm optimization can be combined to resolve the grey model. Practical implications The method exposed in the paper can be used to deal with distribution problems with grey information in the supply chain, and network optimization results with a grey uncertain...