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

作     者：吴静敏 左洪福 陈勇 

作者机构：College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing 210016 China 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2005年第14卷第S2期

页      面：95-101页

核心收录：

学科分类：08[工学] 0806[工学-冶金工程] 082503[工学-航空宇航制造工程] 0825[工学-航空宇航科学与技术] 

主　　题：aircraft design maintenance cost particle swarm optimization immunity algorithm predict 

摘      要：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.