基于时间序列预测的威胁估计方法

doi:10.3785/j.issn.1008-973X.2014.03.004

2014, Vol. 48

Issue (3): 398-403 DOI: 10.3785/j.issn.1008-973X.2014.03.004

计算机技术，无线电电子学

基于时间序列预测的威胁估计方法

赵建军1,王毅2,杨利斌1

1.海军航空工程学院兵器科学与技术系,山东烟台264001；2.海军航空工程学院研究生管理大队,山东烟台 264001

Threat assessment method based on time series forecast

ZHAO Jian-jun1, WANG Yi2, YANG Li-bin1

1.Department of Ordance Science and Technology, Naval Aeronautic and Astronautical Institute, Yantai 264001, China;
2.Graduate Students Brigade, Naval Aeronautic and Astronautical University, Yantai 264001, China

全文: PDF(734 KB)

摘要：

针对在威胁估计的动态贝叶斯网络中,转移概率的获取和观测数据的缺失问题.建立时间序列预测模型,对缺失数据进行预测；在获得完整数据后,利用完整数据集和前向递归算法完成参数学习；通过动态贝叶斯网络对目标的威胁进行估计.仿真结果表明：相比于数学期望最大算法,时间序列方法预测数据精度较高,学习时间短, 能大大提高来袭目标威胁估计的效率,满足实际作战需要.

关键词： 威胁估计; 时间序列; 参数学习; 贝叶斯网络

Abstract:

Aiming at the problems of transition probability getting and observational data missing in dynamic Bayesian network of threat assessment, a time series forecasting model was set up. Then the complete data set and the forward recursive algorithm were applied to parameter learning after the full data got. The threat of target was assessed based on the dynamic Bayesian network. Simulation shows that: compared to the expectation-maximization algorithm, the time series method can get higher accuracy of forecast data, have shorter learning time, increase the efficiency of the threat assessment greatly, and meet the actual operational needs.

Key words: threat assessment time series parameter learning Bayesian network

出版日期: 2014-04-02

TP 391

基金资助:

国家自然科学基金资助项目（61102167）.

作者简介: 赵建军（1963-），男，教授，主要研究方向为武器系统与运用工程：E-mail:wyxh0227@126.com

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引用本文:

赵建军,王毅,杨利斌. 基于时间序列预测的威胁估计方法[J]. J4, 2014, 48(3): 398-403.

ZHAO Jian-jun, WANG Yi, YANG Li-bin. Threat assessment method based on time series forecast. J4, 2014, 48(3): 398-403.

链接本文:

http://www.zjujournals.com/xueshu/eng/CN/10.3785/j.issn.1008-973X.2014.03.004 或 http://www.zjujournals.com/xueshu/eng/CN/Y2014/V48/I3/398

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