| 基于事例推理的海上编队风险评估系统模型 |
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| 引用本文： | 孙永亮,SUN Yong-liang. 基于事例推理的海上编队风险评估系统模型[J]. 指挥控制与仿真, 2005, 27(5): 34-36,45 |
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| 作者姓名： | 孙永亮 SUN Yong-liang |
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| 作者单位： | 海军指挥学院,江苏,南京,210016 |
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| 摘 要： | 海上作战信息范围广、内容多,海上编队面临情况异常复杂.针对海上编队面临的威胁,运用人工智能的基于事例推理技术探索海上编队风险评估问题,建立起了基于事例推理的海上编队风险评估系统模型.该模型运用数据事例库对情报信息进行识别和分析,通过专家对各种情况进行打分,并运行推理机找出相匹配的事例,从而得出海上编队当前的风险指标.该模型能在多种复杂情况中,甄别关键影响因素,通过专家与机器的结合,较准确地定出编队风险值,为指挥员实施判断决策提供帮助.
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| 关 键 词： | 情报处理 基于事例推理 风险评估 舰艇编队 |
| 文章编号： | 1672-7908(2005)05-0034-03 |
| 修稿时间： | 2005-03-24 |
The CBR Model of the Risk Evaluation of Formation on the Sea |
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| SUN Yong-liang. The CBR Model of the Risk Evaluation of Formation on the Sea[J]. Command Control & Simulation, 2005, 27(5): 34-36,45 |
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| Authors: | SUN Yong-liang |
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| Abstract: | Information from operation at sea is of large quantity and of wide range. Allowing for the threat that formation on the sea faces, the case-based reasoning (CBR) model is established to judge the risk of formation on the sea. The model analyzes and identifies all kinds of information in details by case database, reasoning machine and experts. The model can identify the critical influencing factors in complex condition and give the risk evaluation accurately through experts with machines, which can help commanders make right and instant decision. |
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| Keywords: | information processing case-based reasoning risk evaluation ship information |
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