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人工免疫算法路径规划在林火救援中的应用
引用本文:刘丽峰,张树清,李新红.人工免疫算法路径规划在林火救援中的应用[J].吉林大学学报(信息科学版),2012,30(4):433-440.
作者姓名:刘丽峰  张树清  李新红
作者单位:1.山东理工大学 建筑工程学院,山东 淄博250049;2.中国科学院 东北地理与农业生态研究所,长春 130012
基金项目:广东省教育部产学研结合基金资助项目
摘    要:为解决复杂环境下双机林火救援路径规划问题,提出用人工免疫算法规划三维飞行航迹。借鉴人工免疫算法规划机器人路径的方法,通过考虑飞机飞行特性和双机路径规划的要求,为双机异地出发同时到达规划出三维飞行路线,并对算法的主要影响因素进行了分析和估计,获得规划航迹的最优参数,用于设计安全高效的飞行航迹。研究结果表明,该方法能规划出复杂环境下双机飞行航迹,利用参数优化后的人工免疫算法不但能快速有效地规划三维航迹,而且丰富了航迹规划方法研究。

关 键 词:双机三维航迹规划  林火救援  人工免疫算法  最短路径  

Application of Artificial Immune Algorithm in Forest Fire Rescue Path Planning
LIU Li-feng , ZHANG Shu-qing , LI Xin-hong.Application of Artificial Immune Algorithm in Forest Fire Rescue Path Planning[J].Journal of Jilin University:Information Sci Ed,2012,30(4):433-440.
Authors:LIU Li-feng  ZHANG Shu-qing  LI Xin-hong
Institution:1.Institute of Architecture and Engineering,Shandong University of Technology,Zibo 250049,China;2.Northeast Institute of Geography and Agroecology|Chinese Academy of Science,Changchun 130012,China
Abstract:To solve the problem of dual aircrafts path planning for forest fire rescue in complex environment,artificial immune algorithm was proposed for three dimensional flight path planning.Referring to the method of using artificial immune algorithm to plan robot path,three-dimensional flight paths for dual aircrafts were designed by considering the special characteristics of plan and the requirements of dual aircraft path planning in the consideration of taking off at different sites and arrival at desition at the same time,and main factors of the algorithm were analyzed and estimated for finding the optimal parameters of planning track for designing safe and efficient flight path.Results show that the method is capable of planning a dual aricrafts flight path in complex environment.Artificial immune algorithm with optimal parameter will be able to quickly and efficiently planning three-dimensional tracks and enrich the route planning method.
Keywords:dual aircrafts three-dimensional route planning  fire rescue  artificial immune agrithm(AIA)  shortest path
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