全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
电网技术  2011 

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

, PP. 176-182

Keywords: 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

Full-Text   Cite this paper   Add to My Lib

Abstract:

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。

References

[1]  Li Qi,Chen Weirong,Liu Shukui,et al.Mechanism modeling of proton exchange membrane fuel cell based on adaptive focusing particle swarm optimization[J].Proceedings of the CSEE,2009,29(20):119-124(in Chinese).
[2]  陈勇强,刘开培.一种基于径向基函数动态阈值模型的机组状态监测方法[J].中国电机工程学报,2007,27(26):96-101.
[3]  Chen Yongqiang,Liu Kaipei.A condition monitoring method of generators based on RBF dynamic threshold model[J].Proceedings of the CSEE,2007,27(26):96-101(in Chinese).
[4]  王慧强,赖积保,朱亮,等.网络态势感知系统研究综述[J].计算机科学,2006,10(2):5-10.
[5]  Wang Huiqiang,Lai Jibao,Zhu Liang,et al.Survey of network situation awareness system[J].Computer Science,2006,10(2):5-10(in Chinese).
[6]  陈秀镇,郑庆华,管晓宏.层次化网络安全威胁态势量化评估方法[J].软件学报,2006,17(4):885-897.
[7]  Chen Xiuzhen,Zheng Qinghua,Guan Xiaohong.Quantitative hierarchical threat evaluation model for network security[J].Journal of Software,2006,17(4):885-897(in Chinese).
[8]  李雄伟,周希元,杨义先.基于层次分析法的网络攻击效果评估[J].计算机工程与应用,2005,24(49):157-159.
[9]  Li Xiongwei,Zhou Xiyuan,Yang Yixian.Study on the evaluation methods of the attack effect of network based on AHP[J].Computer Engineering and Applications,2005,24(49):157-159(in Chinese).
[10]  邓歆,孟洛明.基于贝叶斯学习的告警相关性分析[J].计算机工程,2007,33(12):40-42.
[11]  Deng Xin,Meng Luoming.Analysis of alarm correlation based on bayesian learning[J].Computer Engineering,2007,33(12):40-42(in Chinese).
[12]  Elattar E E,Goulermas J,Wu Q H.Electric load forecasting based on locally weighted support vector regression[J].IEEE Translations on Systems,Man,and Cybernetics,Part C:Applications and Reviews,2010,40(4):438-447.
[13]  陈涛,龚正虎,胡宁.基于改进BP算法的网络态势预测模型[C]//2009全国计算机网络与通讯学术会议.中国深圳:中国电子学会通信学分会,2009:93-99.
[14]  任伟,蒋兴浩,孙锬锋.基于RBF神经网络的网络安全态势预测方法[J].计算机工程与应用,2006,31(40):136-144.
[15]  Ren Wei,Jiang Xinghao,Sun Tanfeng.RBFNN-based prediction of networks security situation[J].Computer Engineering and Applications,2006,31(40):136-144(in Chinese).
[16]  王晋东,沈柳青,王坤,等.网络安全态势预测及其在智能防护中的应用[J].计算机应用,2010,30(6):1480-1488.
[17]  Wang Jindong,Shen Liuqing,Wang Kun,et al.Network security status forecasting and its application in intelligent defense[J].Journal of Computer Applications,2010,30(6):1480-1488(in Chinese).
[18]  张翔,胡昌振,刘胜航,等.基于支持向量机的网络攻击态势预测技术研究[J].计算机工程,2007,11(3):10-12.
[19]  邓万宇,郑庆华,陈琳,等.神经网络极速学习方法研究[J].计算机学报,2010,2(9):279-287.
[20]  Deng Wanyu,Zheng Qinghua,Chen Lin,et al.Research on extreme learning of neural networks[J].Chinese Journal of Computers,2010,2(9):279-287(in Chinese).
[21]  韩中合,朱霄珣.基于信息熵的支持向量回归机训练样本长度选择[J].中国电机工程学报,2010,30(20):112-116.
[22]  Han Zhonghe,Zhu Xiaoxun.Selection of training sample length in support vector regression based on information entropy[J].Proceedings of the CSEE,2010,30(20):112-116(in Chinese).
[23]  郭创新,朱承治,张琳,等.应用多分类多核学习支持向量机的变压器故障诊断方法[J].中国电机工程学报,2010,30(13):128-134.
[24]  Guo Chuangxin,Zhu Chengzhi,Zhang Lin,et al.A fault diagnosis method for power transformer based on multiclass multiple-kernel learning support vector machine[J].Proceedings of the CSEE,2010,30(13):128-134(in Chinese).
[25]  王雷,张瑞青,盛伟,等.基于支持向量机的回归预测和异常数据检测[J].中国电机工程学报,2009,29(8):92-96.
[26]  Wang Lei,Zhang Ruiqing,Sheng Wei,et al.Regression forecast and abnormal data detection based on support vector regression[J].Proceedings of the CSEE,2009,29(8):92-96(in Chinese).
[27]  杨耿煌,温渤婴.基于量子行为粒子群优化–人工神经网络的电能质量扰动识别[J].中国电机工程学报,2008,28(10):123-129.
[28]  Yao Shuncai,Pan Hongxia.Fractional order PID controller for synchronous machine excitation using particle swarm optimization [J].Proceedings of the CSEE,2010,30(21):91-97(in Chinese).
[29]  李奇,陈维荣,刘述奎,等.基于自适应聚焦粒子群算法的质子交换膜燃料电池机理建模[J].中国电机工程学报,2009,29(20):119-124.
[30]  Zhang Xiang,Hu Changzhen,Liu Shenghang,et al.Research on network attack situation forecast technique based on support vector machine[J].Computer Engineering,2007,11(3):10-12(in Chinese).
[31]  Yang Genghuang,Wen Boying.Identification of power quality disturbance based on QPSO-ANN[J].Proceedings of the CSEE,2008,28(10):123-129(in Chinese).
[32]  姚舜才,潘宏侠.粒子群优化同步电机分数阶鲁棒励磁控制器[J].中国电机工程学报,2010,30(21):91-97.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133