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基于混合遗传算法求解飞机定常状态
引用本文:栾志博,郑淑涛,李洪人.基于混合遗传算法求解飞机定常状态[J].吉林大学学报(工学版),2011,41(1):165-0170.
作者姓名:栾志博  郑淑涛  李洪人
作者单位:哈尔滨工业大学机电工程学院,哈尔滨,150001
基金项目:教育部新世纪优秀人才支持计划项目(NCET-04-0325).
摘    要:为保证对飞机定常状态准确求解,在分析了定常状态的基本特性和相应约束条件的基础上,提出了一种新的混合遗传算法.算法基于"学习潜能"的概念将遗传算法中的拉马克学习与鲍德温学习两种学习机制有机结合在一起,将局部搜索次数在群体中进行合理分配,使学习的优势得到充分发挥,使其不足得到有效抑制.本文算法不依赖于飞机动力学模型的具体形...

关 键 词:人工智能  遗传算法  定常飞行状态  个体学习潜能  拉马克学习  鲍德温学习
收稿时间:2009-01-15

Solution of steady state of aircraft based on mixture genetic algorithm
LUAN Zhi-bo,ZHENG Shu-tao,LI Hong-ren.Solution of steady state of aircraft based on mixture genetic algorithm[J].Journal of Jilin University:Eng and Technol Ed,2011,41(1):165-0170.
Authors:LUAN Zhi-bo  ZHENG Shu-tao  LI Hong-ren
Affiliation:School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
Abstract:To obtain the accurate solutions of the steady state of aircraft, a hybrid genetic algorithm was proposed according to the analysis of the basic characteristics and constraints of the steady state. Based on the concept of “individual learning potentiality”, this algorithm logistically integrates the Lamarckian learning and Baldwinian learning mechanisms. It rationally distributes the number of local search among the population to make the advantage of the learning into full play, meanwhile inhibit its disadvantage. The algorithm can solve any preassigned steady state on the basis of the state variables rather than the real form of the aerodynamic model. Simulation results validate the proposed algorithm that combines the two learning mechanisms.
Keywords:artificial intelligence  genetic algorithm  steady flight state  individual learning potentiality  Lamarckian learning  Baldwinina learning
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