| 主动推送模式下的情报需求预测模型 |
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| 引用本文： | 管清波,冯书兴. 主动推送模式下的情报需求预测模型[J]. 系统仿真技术, 2012, 8(4): 300-304 |
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| 作者姓名： | 管清波 冯书兴 |
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| 作者单位： | 1. 装备学院航天指挥系,北京,101416
2. 装备学院训练部,北京,101416 |
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| 基金项目： | 国家"八六三"高技术研究发展计划资助项目 |
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| 摘 要： | 针对主动推送模式下的情报需求预测问题,提出了基于案例推理的解决方案。设计了进行情报需求预测案例分析的工作流程,建立了案例属性描述模型;应用最近邻法进行案例的相似度评价,并通过信息增益的计算确定每个属性的权值,获得相似案例(集);提出了方案调整和推理策略。
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| 关 键 词： | 案例推理 情报需求 最近邻法 信息增益 |
A Model of Intelligence Requirement Forecasting for the Active Push Mode |
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| GUAN Qingbo , FENG Shuxing. A Model of Intelligence Requirement Forecasting for the Active Push Mode[J]. System Simulation Technology, 2012, 8(4): 300-304 |
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| Authors: | GUAN Qingbo FENG Shuxing |
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| Affiliation: | 1. Department of Space Command,the Academy of Equipment,Beijing 101416 ,China 2. Department of Training, the Academy of Equipment, Beijing 101416, China) |
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| Abstract: | This paper presents a method-cased-based reasoning to settle the problem of intelligence requirement forecasting for the active push mode. First, a work process of case analysis is designed ,and a model is built to describe case attributes. Second, employing K-Nearest Neighbor （K-NN） algorithm combined with information gain method, similarity between cases is evaluated. Finally, some policies are present to adjust and reason the similar case（s） |
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| Keywords: | cased-based reasoning intelligence requirement forecasting K-Nearest Neighbor （K-NN）algorithm information gain |
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