| 基于贝叶斯网络和蚁群算法的航路优化 |
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| 引用本文： | 葛艳,税薇,韩玉,魏振钢. 基于贝叶斯网络和蚁群算法的航路优化[J]. 计算机工程, 2009, 35(12): 175-177 |
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| 作者姓名： | 葛艳 税薇 韩玉 魏振钢 |
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| 作者单位： | 青岛科技大学信息科学技术学院,青岛,266061;青岛科技大学自动化学院,青岛,266042;海军航空工程学院青岛分院虚拟仿真研究室,青岛,266041;中国海洋大学计算机科学系,青岛,266071 |
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| 基金项目： | 国家自然科学基金，青岛科技大学校科研启动基金 |
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| 摘 要： | 为了提高无人机（UAV）的作战效率和生存概率,在UAV执行任务前,必须为其设计高效的飞行航路。采用将贝叶斯网络模型威胁强度评估算法与蚁群算法相结合的航路规划方法,根据UAV航路规划问题的特点对蚁群算法进行改进。仿真结果表明,该方法能更好地满足实时战场需要,得到良好的优化航路。
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| 关 键 词： | 贝叶斯网络 评估算法 威胁强度 蚁群算法 |
| 修稿时间： | |
Route Optimization Based on Bayesian Network and Ant Colony Algorithm |
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| GE Yan,SHUI Wei,HAN Yu,WEI Zhen-gang. Route Optimization Based on Bayesian Network and Ant Colony Algorithm[J]. Computer Engineering, 2009, 35(12): 175-177 |
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| Authors: | GE Yan SHUI Wei HAN Yu WEI Zhen-gang |
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| Affiliation: | 1.School of Information Science and Technology;Qingdao University of Science & Technology;Qingdao 266061;2.School of Automation;Qingdao 266042;3.Virtual Simulation Lab;Qingdao Branch;Naval Aeronautic Engineering Academy;Qingdao 266041;4.Dept.of Computer Science;Ocean University of China;Qingdao 266071 |
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| Abstract: | In order to improve operational efficiency and survival probability of Unmanned Air Vehicle(UAV),efficient route must be designed before the UAV performs a mission.This paper uses route planning method which combines the threat intensity assessment algorithm for Bayesian network model and ant colony algorithm.Ant colony algorithm is improved according to characteristic of UAV route planning.Simulation results show that this method can satisfy the needs of real-time battlefield better and get a favorable opt... |
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| Keywords: | Bayesian network assessment algorithm threat intensity ant colony algorithm |
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