吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (04): 1064-1069.doi: 10.7964/jdxbgxb201304035

• paper • Previous Articles     Next Articles

Target threat assessment using glowworm swarm optimization and BP neural network

WANG Gai-ge1,2, GUO Li-hong1, DUAN Hong3, LIU Luo1,2, WANG He-qi1   

  1. 1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100039, China;
    3. School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
  • Received:2012-06-07 Online:2013-07-01 Published:2013-07-01

RICH HTML

0   

PDF (PC)

553

Abstract:

Based on the introduction of Glowworm Swarm Optimization (GSO) and Back-Propagation (BP) neural network, a target threat assessment model is proposed and its algorithm is developed. This model is based on GSO optimized BP network (GSOBP). In GSOBP, GSO is employed to simultaneously optimize the initial weights and thresholds of the BP neural network. Target threat database is adopted to test the performance of GSOBP in target threat prediction. The performance of GSOBP is compared with that of normal BP neural network and Particle Swarm Optimization and Support Vector Machines (PSO_SVM). Experiment results show that target threat prediction accuracy by GSOBP is higher than that by normal BP or by PSO_SVM.

Key words: computer application, back propagation neural network, target threat assessment, glowworm swarm optimization

CLC Number: 

  • TP391.9

[1] 雷英杰. 基于直觉模糊推理的态势与威胁评估研究. 西安:西安电子科技大学, 2005. Lei Ying-jie. Research on situation and threat assessment based on intuitionistic fuzzy reasoning. Xi'an: Xidian University, 2005.

[2] 杨健, 高文逸, 刘军. 一种基于贝叶斯网络的威胁估计方法[J]. 解放军理工大学学报:自然科学版, 2010, 11(1): 43-48. Yang Jian, Gao Wen-yi, Liu Jun. Threat assessment method based on Bayesian network[J]. Journal of PLA University of Science and Technology(Natural Edition), 2010, 11(1): 43-48.

[3] 王晓帆, 王宝树. 基于直觉模糊与计划识别的威胁评估方法[J]. 计算机科学, 2010, 37(5): 175-177. Wang Xiao-fan, Wang Bao-shu. Techniques for threat assessment based on intuitionistic fuzzy theory and plan recognition[J]. Computer Science, 2010, 37(5):175-177.

[4] 王改革, 郭立红, 段红, 等. 基于Elman_AdaBoost强预测器的目标威胁评估模型及算法[J]. 电子学报, 2012, 40(5): 901-906. Wang Gai-ge, Guo Li-hong, Duan Hong, et al. The model and algorithm for the target threat assessment based on Elman_AdaBoost strong predictor[J]. Acta Electronica Sinica, 2012, 40(5): 901-906.

[5] 龚勃文, 林赐云, 李静, 等. 基于核自组织映射-前馈神经网络的交通流短时预测[J]. 吉林大学学报:工学版, 2011, 41(4): 938-943. Gong Bo-wen, Lin Ci-yun, Li Jing, et al. Short-term traffic flow prediction based on KSOM-BP neural network[J]. Journal of Jilin University (Engineering and Technology Edition), 2011, 41(4): 938-943.

[6] 赵宏伟, 齐一名, 臧雪柏, 等. 基于系统辨识与T-S模糊神经网络的磨矿分级控制[J]. 吉林大学学报:工学版, 2011, 41(1): 171-175. Zhao Hong-wei, Qi Yi-ming, Zang Xue-bai, et al. Control of milling classification using system identification and T-S fuzzy neural network[J]. Journal of Jilin University (Engineering and Technology Edition), 2011, 41(1): 171-175.

[7] 刘大有, 张冬威, 李妮娅, 等. 基于网络聚类选择的神经网络集成方法及应用[J]. 吉林大学学报:工学版, 2011, 41(4): 1034-1040. Liu Da-you, Zhang Dong-wei, Li Ni-ya, et al. Selective approach for neural network ensemble based on network clustering technology and its application[J]. Journal of Jilin University (Engineering and Technology Edition), 2011, 41(4): 1034-1040.

[8] 许新征, 丁世飞, 史忠植, 等. 图像分割的新理论和新方法[J]. 电子学报, 2010, 38(2A):76-82. Xu Xin-zheng, Ding Shi-fei, Shi Zhong-zhi, et al. New theories and methods of image segmentation[J]. Acta Electronica Sinica, 2010, 38(2A):76-82.

[9] 罗艳春, 郭立红, 姜晓莲, 等. 基于模糊神经网络的空中目标威胁估计[J]. 微计算机信息, 2007, 23(34): 268-270. Luo Yan-chun, Guo Li-hong, Jiang Xiao-lian, et al. Threat assessment for aerial target based on fuzzy neural network[J]. Microcomputer Information, 2007, 23(34):268-270.

[10] Krishhand K N, Ghose D. Glowworm swarm optimization for simultaneous capture of multiple local optimal of muultimodal functions[J]. Swarm Intelligence, 2009, 3(2): 87-124.

[11] Kennedy J, Eberhart R. Particle swarm optimization//Proceeding of the IEEE International Conference on Neural Networks, Perth, Australia, 1995.

[12] Chang C C, Lin C J. LIBSVM: a library for support vector machines[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2011, 2(3): 1-27.
[1] LIU Fu,ZONG Yu-xuan,KANG Bing,ZHANG Yi-meng,LIN Cai-xia,ZHAO Hong-wei. Dorsal hand vein recognition system based on optimized texture features [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1844-1850.
[2] WANG Li-min,LIU Yang,SUN Ming-hui,LI Mei-hui. Ensemble of unrestricted K-dependence Bayesian classifiers based on Markov blanket [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1851-1858.
[3] JIN Shun-fu,WANG Bao-shuai,HAO Shan-shan,JIA Xiao-guang,HUO Zhan-qiang. Synchronous sleeping based energy saving strategy of reservation virtual machines in cloud data centers and its performance research [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1859-1866.
[4] ZHAO Dong,SUN Ming-yu,ZHU Jin-long,YU Fan-hua,LIU Guang-jie,CHEN Hui-ling. Improved moth-flame optimization method based on combination of particle swarm optimization and simplex method [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1867-1872.
[5] LIU En-ze,WU Wen-fu. Agricultural surface multiple feature decision fusion disease judgment algorithm based on machine vision [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1873-1878.
[6] OUYANG Dan-tong, FAN Qi. Clause-level context-aware open information extraction [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1563-1570.
[7] LIU Fu, LAN Xu-teng, HOU Tao, KANG Bing, LIU Yun, LIN Cai-xia. Metagenomic clustering method based on k-mer frequency optimization [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1593-1599.
[8] GUI Chun, HUANG Wang-xing. Network clustering method based on improved label propagation algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1600-1605.
[9] LIU Yuan-ning, LIU Shuai, ZHU Xiao-dong, CHEN Yi-hao, ZHENG Shao-ge, SHEN Chun-zhuang. LOG operator and adaptive optimization Gabor filtering for iris recognition [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1606-1613.
[10] CHE Xiang-jiu, WANG Li, GUO Xiao-xin. Improved boundary detection based on multi-scale cues fusion [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1621-1628.
[11] ZHAO Hong-wei, LIU Yu-qi, DONG Li-yan, WANG Yu, LIU Pei. Dynamic route optimization algorithm based on hybrid in ITS [J]. 吉林大学学报(工学版), 2018, 48(4): 1214-1223.
[12] HUANG Hui, FENG Xi-an, WEI Yan, XU Chi, CHEN Hui-ling. An intelligent system based on enhanced kernel extreme learning machine for choosing the second major [J]. 吉林大学学报(工学版), 2018, 48(4): 1224-1230.
[13] FU Wen-bo, ZHANG Jie, CHEN Yong-le. Network topology discovery algorithm against routing spoofing attack in Internet of things [J]. 吉林大学学报(工学版), 2018, 48(4): 1231-1236.
[14] CAO Jie, SU Zhe, LI Xiao-xu. Image annotation method based on Corr-LDA model [J]. 吉林大学学报(工学版), 2018, 48(4): 1237-1243.
[15] HOU Yong-hong, WANG Li-wei, XING Jia-ming. HTTP-based dynamic adaptive streaming video transmission algorithm [J]. 吉林大学学报(工学版), 2018, 48(4): 1244-1253.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd