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基于多种群粒子群算法的舰船消磁决策优化
引用本文:刘宏达,马忠丽,李殿璞.基于多种群粒子群算法的舰船消磁决策优化[J].船舶工程,2007,29(2):42-45.
作者姓名:刘宏达  马忠丽  李殿璞
作者单位:哈尔滨工程大学,自动化学院,哈尔滨,150001
摘    要:随着舰船消磁技术的发展,消磁线圈的数目越来越多,调整消磁系统的常规方法越来越难以实施.为解决这一问题,提出一种改进的粒子群算法,该方法利用多种群搜索策略来压缩搜索空间,从而有效提高得到全局最优解的概率.仿真结果表明:该算法在舰船消磁磁场特征均方根最小和峰值最小方面均比其他方法更有优势,此外,该算法具有计算方法直观,编程简单,计算速度快,全局解搜索率高,易于进行多机协作的优点,可以方便地应用于工程实际.

关 键 词:舰船  消磁  多种群算法  粒子群优化
文章编号:1000-6982(2007)02-0042-04
修稿时间:2006-04-18

Optimization of warship degaussing decision based on poly-population particle swarm algorithm
LIU Hong-d,MA Zhong-li,LI Dian-pu.Optimization of warship degaussing decision based on poly-population particle swarm algorithm[J].Ship Engineering,2007,29(2):42-45.
Authors:LIU Hong-d  MA Zhong-li  LI Dian-pu
Institution:Automation College, Harbin Engineering University, Harbin 150001, China
Abstract:With the development of warship degaussing technology, the number of degaussing coils gets more and more, and conventional methods of calibrating degaussing systems are more and more difficult to implement. To solve this problem, an improved particle swarm algorithm is proposed, which adopts the search strategy of poly-population particle to compress search space to improve the probability of searching global optimization solution. The simulation results show that this algorithm has more advantages than others in terms of minimizing the root mean square and peak of the warship degaussing magnetic field signature. In addition, this algorithm has many excellences such as intuitional algorithm, simple program, fast computation speed and high global searching probability, which make it easy to collaborate multi-computer and be applied to real projects.
Keywords:warship  degaussing  poly-population algorithm  particle swarm optimization
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