The Algorithm of Power System Security Detection Comprehensive Decision Based on Dempster-Shafer Theory Improved Combination Rule
Liu Jia1, Xu Guoai1, Gao Yang1, Yang Yixian1, Cheng Gong2
1. Beijing University of Posts and Telecommunications Beijing 100876 China 2. National Computer Network and Information Security Administration Center Beijing 100029 China
Abstract:To evaluate whether the construction of power secondary system classified protection reaches the standard, we take Dempster-Shafer theory to combine the security detection results. In the process of studying rule of combination, it is found that the original rule isn’t very effective in handling the evidence with high degree of conflict. There have been several improvement methods but their effects aren’t very ideal. Therefore, this paper proposes the concept of average of conflict’s volatility between evidence. We design a novel combination rule of Dempster-Shafer theory based on it and establish a modified algorithm of comprehensive decision. This algorithm can solve the problem of the high degree conflict between evidence and reduce the affection of uncertainty factors more effectively than others so that it can obtain a better compliance decision result and protect the running of power primary and secondary system.
刘嘉, 徐国爱, 高洋, 杨义先, 程工. 基于证据理论改进合成法则的电力系统安全检验综合判定算法[J]. 电工技术学报, 2011, 26(7): 247-255.
Liu Jia, Xu Guoai, Gao Yang, Yang Yixian, Cheng Gong. The Algorithm of Power System Security Detection Comprehensive Decision Based on Dempster-Shafer Theory Improved Combination Rule. Transactions of China Electrotechnical Society, 2011, 26(7): 247-255.
[1] 国家电力监管委员会. 电力行业信息系统安全等级保护定级工作指导意见. 2007. [2] 章小强, 管霖, 王同文. 针对特征选择问题的改进蚁群算法及其在电力系统安全评估中的应用[J]. 电工技术学报, 2010, 25(12): 154-160. Zhang Xiaoqiang, Guan Lin, Wang Tongwen. Kernel feature identification based on improved ant colony optimization algorithm for transient stability assessment[J]. Transactions of China Electrotechnical Society, 2010, 25(12): 154-160. [3] 国家电力监管委员会. 电力二次系统安全防护规定. 2008. [4] Yager R R. On the dempster-shafer framework and new combination rules[J]. Information Science, 1987, 41: 93-137. [5] Inagaki T. Interdependence between safety-control police and multiple-sensor schemes via dempster- shafer theory[J]. IEEE Transactions on Reliability, 1991, 40(2): 182-188. [6] 孙全, 叶秀清, 顾伟康. 一种新的基于证据理论的合成公式[J]. 电子学报, 2000, 28(8): 117-119. Sun Quan, Ye Xiuqing, Gu Weigang. A new combination rule of evidence[J]. Acta Electronica Sinica, 2000, 28(8): 117-119. [7] 向阳, 史习智. 证据理论合成发展的一点修正[J]. 上海交通大学学报, 1999, 33(3): 357-360. Xiang Yang, Shi Xizhi. Modification on combination rules of evidence theory[J]. Journal of Shanghai Jiaotong University, 1999, 33(3): 357-360. [8] 邓勇, 施文康. 一种改进的证据推理组合规则[J]. 上海交通大学学报. 2003, 37(8): 1275-1278. Deng Yong, Shi Wenkang. A modified combiantion rule of evidence theory[J]. Journal of Shanghai Jiaotong University, 2003, 37(8): 1275-1278. [9] 杜峰, 施文康, 邓勇. 证据特征提取及其在证据理论改进中的应用[J]. 上海交通大学学报. 2004, 38(增刊): 164-168. Du Feng, Shi Wenkang, Deng Yong. Feature extraction of evidence and its application in modification of evidence theory[J]. Journal of Shanghai Jiaotong University, 2004, 38(z1): P164-168. [10] Smets P. The combination of evidence in the transferable belief model[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1990, 12(5): 447-458. [11] Sentz K. Combination of evidence in dempster- shafer theory[M]. New York: Binghamton University Press, 2002. [12] Liu Vanqiong, Chen Yingwu, Gao Feng, et al. Risk evaluation using evidence reasoning theory[C]. 2005 International Conference on Machine Learning and Cybernetics(ICMLC 2005), 2005: 2855-2860. [13] 高会生, 朱静. 基于D-S证据理论的网络安全风险评估模型[J]. 计算机工程与应用, 2008, 44(6): 754-759. Gao Huisheng, Zhu Jing. Security risk assessment model of network based on D-S evidence theory[J]. Computer Engineering and Application, 2008, 44: 754-759. [14] Shafer G. A mathematical theory of evidence[M]. New Jersey: Princeton University Press, Princeton, 1976. [15] Murphy C K. Combining belief fuctions when evidence Conflicts[J]. Decision Support Systems, 2000, 29(1): 1-9. [16] Dempster A P. A generalization of bayesian inference (with discussion)[J]. Journal of the Royal Statistical Society Series B, 1968, 30(2): 205-247. [17] Bae H R, Grandhi R V, Canfield R A. Sensitivity analysis of structural response uncertainty propagation using evidence theory[J]. Structural and Multidisciplinary Optimization, 2006, 31(4): 270-279. [18] 孙怀江, 杨静宇. 一种相关证据合成方法[J]. 计算机学报, 1999, 22(9): 1004-1007. Sun Huaijiang, Yang Jingyu. A combination method for dependent evidences[J]. Chinese Journal of Computers, 1999, 22(9): 1004-1007. [19] 李弼程, 王波, 魏俊, 等. 一种有效的证据理论合成公式[J]. 数据采集与处理, 2002, 17(1): 33-36. Li Bicheng, Wang Bo, Wei Jun, et al. An efficient combination rule of evidence theory[J]. Journal of Data Acquisition & Processing, 2002, 17(1): 33-36. [20] 佘二永, 王润生, 徐学文. 基于预处理模式的D-S证据理论改进方法[J]. 模式识别与人工智能, 2007, 20(5): 711-715. She Eryong, Wang Runsheng, Xu Xuewen. An improved method of D-S evidence theory based on pretreatment mode[J]. Pattern Recognition And Artificial Intelligence, 2007, 20(5): 711-715.