| Target distribution in cooperative combat based on Bayesian optimization algorithm |
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| 引用本文： | Shi Zhifu,Zhang An & Wang Anli Electronic Information School,Northwestern Polytechnical Univ.,Xi’an 710072,P. R. China. Target distribution in cooperative combat based on Bayesian optimization algorithm[J]. 系统工程与电子技术(英文版), 2006, 17(2): 339-342. DOI: 10.1016/S1004-4132(06)60059-5 |
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| 作者姓名： | Shi Zhifu Zhang An & Wang Anli Electronic Information School Northwestern Polytechnical Univ. Xi’an 710072 P. R. China |
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| 作者单位： | Shi Zhifu，Zhang An & Wang Anli Electronic Information School，Northwestern Polytechnical Univ.，Xi’an 710072，P. R. China |
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| 基金项目： | This project was supported by the Fund of College Doctor Degree (20020699009) |
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| 摘 要： | 1 .INTRODUCTIONThe target distributionis one of difficult content incooperation air combat . The missionis fully exertsthe whole advantage of all firepower units . Thedistributionis finding the best schedule which ac-cord with distribution principles at the moment ofgiven conditions .It can make finitely weapons gainthe best effective through opti mizing method. Theresult is that the effective of weaponis best andthewhole benefits are highest .But the target distribu-tionis restricted wi…
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| 收稿时间： | 2005-01-19 |
Target distribution in cooperative combat based on Bayesian optimization algorithm |
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| Shi Zhifu,Zhang An,Wang Anli. Target distribution in cooperative combat based on Bayesian optimization algorithm[J]. Journal of Systems Engineering and Electronics, 2006, 17(2): 339-342. DOI: 10.1016/S1004-4132(06)60059-5 |
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| Authors: | Shi Zhifu Zhang An Wang Anli |
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| Affiliation: | 1. School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 10081, China;2. School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 10081, China |
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| Abstract: | Target distribution in cooperative combat is a difficult and emphases. We build up the optimization model according to the rule of fire distribution. We have researched on the optimization model with BOA. The BOA can estimate the joint probability distribution of the variables with Bayesian network, and the new candidate solutions also can be generated by the joint distribution. The simulation example verified that the method could be used to solve the complex question, the operation was quickly and the solution was best. |
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| Keywords: | target distribution Bayesian network Bayesian optimization algorithm cooperative air combat |
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