| 基于支持向量机和粒子群算法的信息网络安全态势复合预测模型 |
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| 引用本文： | 高昆仑,刘建明,徐茹枝,王宇飞,李怡康.基于支持向量机和粒子群算法的信息网络安全态势复合预测模型[J].电网技术,2011(4):176-182. |
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| 作者姓名： | 高昆仑 刘建明 徐茹枝 王宇飞 李怡康 |
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| 作者单位： | 中国电力科学研究院信息与通信研究所;国网信息通信有限公司;华北电力大学控制与计算机工程学院; |
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| 基金项目： | 国家电网公司科技项目(B11-09-109) |
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| 摘 要： | 提出一种基于支持向量机和粒子群算法的网络态势复合预测模型。模型使用滑动窗口方法将各原始离散时间监测点的安全态势值构造成部分线性相关的连续时间序列,以其作为安全态势数据样本集对支持向量机加以训练,生成预测模型。在支持向量机训练过程中,利用粒子群算法搜寻支持向量机的最优训练参数,以降低支持向量机参数选择的盲目性,提高预测精度。最后通过基于大量电力企业信息网络现场安全监测数据的实验,验证了复合预测模型的有效性。
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| 关 键 词： | 信息网络安全态势 回归预测 支持向量机 粒子群算法 时间序列 |
A Hybrid Security Situation Prediction Model for Information Network Based on Support Vector Machine and Particle Swarm Optimization |
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| GAO Kunlun,Liu Jianming,XU Ruzhi,WANG Yufei,LI Yikang.A Hybrid Security Situation Prediction Model for Information Network Based on Support Vector Machine and Particle Swarm Optimization[J].Power System Technology,2011(4):176-182. |
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| Authors: | GAO Kunlun Liu Jianming XU Ruzhi WANG Yufei LI Yikang |
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| Affiliation: | GAO Kunlun1,Liu Jianming2,XU Ruzhi3,WANG Yufei3,LI Yikang3(1.Information & Communication Department of China Electric Power Research Institute,Hardian District,Beijing 100192,China,2.State Grid Information & Telecommunication Company Limited,Xuanwu District,Beijing 100761,3.School of Control and Computer Engineering,North China Electric Power University,Changping District,Beijing 102206,China) |
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| Abstract: | A security situation prediction model for information network based on support vector machine(SVM) and particle swarm optimization(PSO) is proposed.By use of sliding window,in the proposed model a continuous time series that is partially linearly dependent is constructed by security situation values sampled from original discrete time monitoring points,and taking the time series as the sample set of security situation data the SVM is trained to generate a prediction model.During the training of SVM,the PSO ... |
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| Keywords: | security situation of information network regression prediction support vector machine particle swarm optimization time series |
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