An estimation method for direct maintenance cost of aircraft components based on particle swarm optimization with immunity algorithm

来源期刊：中南大学学报(英文版)2005年第z2期

论文作者：吴静敏 左洪福 陈勇

文章页码：95 - 101

Key words：aircraft design； maintenance cost； particle swarm optimization； immunity algorithm； predict

Abstract: A particle swarm optimization (PSO) algorithm improved by immunity algorithm (IA) was presented. Memory and self-regulation mechanisms of IA were used to avoid PSO plunging into local optima. Vaccination and immune selection mechanisms were used to prevent the undulate phenomenon during the evolutionary process. The algorithm was introduced through an application in the direct maintenance cost (DMC) estimation of aircraft components. Experiments results show that the algorithm can compute simply and run quickly. It resolves the combinatorial optimization problem of component DMC estimation with simple and available parameters. And it has higher accuracy than individual methods, such as PLS, BP and v-SVM, and also has better performance than other combined methods, such as basic PSO and BP neural network.