基于软计算的IP网络流量监测和控制关键技术研究
|
摘要
伴随互联网技术和网络业务的迅速发展，互联网已成为科研生产及人们日常生活中不可或缺的组成部分。快速有效的数据传输对于互联网中的实时业务，例如多媒体视频、VoIP等，以及以文件下载为代表的非实时业务，都具有非常重要的意义。因此，如何充分利用现有带宽、以最小代价的资源开销获取最优化的应用效果，是业界当前的研究热点。IP网络监测及控制技术的应用为在现有条件下提供更优质的网络服务开辟了一条行之有效的途径，本课题以此为突破，结合神经网络、基因表达式等软计算技术，对网络流量监测模型的建立，预测算法的设计和流量控制的实现进行了深入研究：
（1）提出了一种新的基于代理的互联网QoS流量监测模型，阐述了该模型的体系结构和实现功能，在完成系统分析的基础上对监测模型的组件设计及实现进行研究。作者以VoIP业务作为研究对象，基于该模型完成对VoIP业务中的QoS监测，并对呼叫详细记录的关联合成算法进行优化。
（2）在基于BP神经网络的IP网络流量预测算法基础上，结合基因表达式编程进化算法的优势，提出了基于进化BP的IP网络流量预测算法，作者针对该算法的编码、遗传操作及算法描述做了详细分析，并与传统算法进行了比较仿真实验和性能分析，实验证实，本文提出的预测算法能够更好地解决BP算法固有的训练速度慢，易陷入局部最优以及全局搜索能力弱等缺陷。
（3）提出了基于小波变换和GFARIMA模型的流量预测算法，该算法将经过处理后的原始流量进行小波分解，分别对近似分量和细节分量完成单支重构，并对重构后的细节分量和近似分量用GFARIMA模型进行预测，并合成最终预测流量，该算法较之以前的算法具备更高的预测准确度，且解决了FARIMA模型时间滞后效应带来的问题。
（4）提出了基于模拟退火基因表达式编程的路由选择最优化算法。该算法在使用基因表达式编程算法进行多目标函数优化时，对初始种群中的每一个个体进行模拟退火操作，然后再进行一系列其它的遗传操作及适应度函数评价。文章针对模拟退火算法容易跳出局部最优解的缺陷，提出了基于模拟退火基因表达式编程的路由选择最优化算法，该算法能够更好地解决单一基因表达式编程优化精度差、易陷入局部最优的问题。作者在使用基因表达式编程算法进行多目标函数优化时，对初始种群中的每一个个体进行模拟退火操作，然后再进行一系列其它的遗传操作及适应度函数评价。
综上所述，本文从监测模型的建立、预测算法的研究到QoS流量控制的提出，给出了一整套IP网络流量监测和控制的解决方案，并以仿真的形式验证了方案的可行性，对现实场景下的商业应用具有很好的启发作用。
Accompanied by the rapid development of Internet technology and network applications,the Internet has become an indispensable part of scientific research and people’s daily life. Itis extremely important to transmit data rapidly and effectively in the Internet for the real-timeservice, such as multimedia video and VoIP, as well as the transmission of non real-timeservice like file-downloading. Therefore, achieving the optimal use with minimum cost of thenetwork resource is one of the focus research areas today. IP network monitoring and controltechnology provides an effective way to transmit data in a limited network bandwidthenvironment with better services. Combining with soft computing technique, this thesisstudies the monitoring model, traffic prediction algorithms and flow control method of theInternet：
(1) An Internet QoS monitoring model based on agent technology is proposed in thisthesis and the structure and function of the model is described. Based on it, the componentdesign and implementation of the model is also discussed. Being as the research object of themodel, the QoS of VoIP services is studied and the algorithm of the call detail records isoptimized.
(2) Combined with the advantages of gene expression programming, an ITF-EBPalgorithm (Internet Traffic Forecasting Based on Evolutionary BP Neural Network) is putforwarded in the thesis which is based on BP neural network-based IP network trafficprediction algorithm. The thesis describes the encoding, the genetic manipulation and thealgorithm exhaustively. Compared with the traditional algorithm, ITF-EBP could improve thetraining speed and global search capability. Simulation and performance analysis prove it.The thesis describes the encoding, the genetic manipulation and the algorithm exhaustively,and compares the simulation and performance analysis with the traditional algorithm.
(3) Based on studies on the wavelet transform and FARIMA technology, a networktraffic prediction algorithm based on wavelet transform and modified GFARIMA model isproposed in the thesis. This algorithm decomposes the original flow after its treatment,reconstructs the detail component and the approximate component respectively, predicts each component via modified GFARIMA prediction algorithm, and synthesis the flow. It improvesthe accuracy of the prediction algorithm and partly eliminates the lagging effect of theoriginal method.
(4) An ORS-SAGEP (Optimization for Route Selection based on Simulated AnnealingGene Expression Programming) algorithm based on ORS-GEP (Optimization for RouteSelection based on Gene Expression Programming) algorithm is brought forward in thisthesis. As for the advantages of easy jumping out from local optimal solution of the geneexpression programming, ORS-SAGEP could improve the programming accuracy, and thesimulation results prove its performance.
In conclusion, thesis provides a whole set of IP network traffic monitoring and controlsolution, it describes the establishment of the monitoring model, the network trafficprediction algorithm and the QoS flow control. The solution has been verified the feasibility,and it can play an objective inspiration in actual scene
（1）提出了一种新的基于代理的互联网QoS流量监测模型，阐述了该模型的体系结构和实现功能，在完成系统分析的基础上对监测模型的组件设计及实现进行研究。作者以VoIP业务作为研究对象，基于该模型完成对VoIP业务中的QoS监测，并对呼叫详细记录的关联合成算法进行优化。
（2）在基于BP神经网络的IP网络流量预测算法基础上，结合基因表达式编程进化算法的优势，提出了基于进化BP的IP网络流量预测算法，作者针对该算法的编码、遗传操作及算法描述做了详细分析，并与传统算法进行了比较仿真实验和性能分析，实验证实，本文提出的预测算法能够更好地解决BP算法固有的训练速度慢，易陷入局部最优以及全局搜索能力弱等缺陷。
（3）提出了基于小波变换和GFARIMA模型的流量预测算法，该算法将经过处理后的原始流量进行小波分解，分别对近似分量和细节分量完成单支重构，并对重构后的细节分量和近似分量用GFARIMA模型进行预测，并合成最终预测流量，该算法较之以前的算法具备更高的预测准确度，且解决了FARIMA模型时间滞后效应带来的问题。
（4）提出了基于模拟退火基因表达式编程的路由选择最优化算法。该算法在使用基因表达式编程算法进行多目标函数优化时，对初始种群中的每一个个体进行模拟退火操作，然后再进行一系列其它的遗传操作及适应度函数评价。文章针对模拟退火算法容易跳出局部最优解的缺陷，提出了基于模拟退火基因表达式编程的路由选择最优化算法，该算法能够更好地解决单一基因表达式编程优化精度差、易陷入局部最优的问题。作者在使用基因表达式编程算法进行多目标函数优化时，对初始种群中的每一个个体进行模拟退火操作，然后再进行一系列其它的遗传操作及适应度函数评价。
综上所述，本文从监测模型的建立、预测算法的研究到QoS流量控制的提出，给出了一整套IP网络流量监测和控制的解决方案，并以仿真的形式验证了方案的可行性，对现实场景下的商业应用具有很好的启发作用。
Accompanied by the rapid development of Internet technology and network applications,the Internet has become an indispensable part of scientific research and people’s daily life. Itis extremely important to transmit data rapidly and effectively in the Internet for the real-timeservice, such as multimedia video and VoIP, as well as the transmission of non real-timeservice like file-downloading. Therefore, achieving the optimal use with minimum cost of thenetwork resource is one of the focus research areas today. IP network monitoring and controltechnology provides an effective way to transmit data in a limited network bandwidthenvironment with better services. Combining with soft computing technique, this thesisstudies the monitoring model, traffic prediction algorithms and flow control method of theInternet：
(1) An Internet QoS monitoring model based on agent technology is proposed in thisthesis and the structure and function of the model is described. Based on it, the componentdesign and implementation of the model is also discussed. Being as the research object of themodel, the QoS of VoIP services is studied and the algorithm of the call detail records isoptimized.
(2) Combined with the advantages of gene expression programming, an ITF-EBPalgorithm (Internet Traffic Forecasting Based on Evolutionary BP Neural Network) is putforwarded in the thesis which is based on BP neural network-based IP network trafficprediction algorithm. The thesis describes the encoding, the genetic manipulation and thealgorithm exhaustively. Compared with the traditional algorithm, ITF-EBP could improve thetraining speed and global search capability. Simulation and performance analysis prove it.The thesis describes the encoding, the genetic manipulation and the algorithm exhaustively,and compares the simulation and performance analysis with the traditional algorithm.
(3) Based on studies on the wavelet transform and FARIMA technology, a networktraffic prediction algorithm based on wavelet transform and modified GFARIMA model isproposed in the thesis. This algorithm decomposes the original flow after its treatment,reconstructs the detail component and the approximate component respectively, predicts each component via modified GFARIMA prediction algorithm, and synthesis the flow. It improvesthe accuracy of the prediction algorithm and partly eliminates the lagging effect of theoriginal method.
(4) An ORS-SAGEP (Optimization for Route Selection based on Simulated AnnealingGene Expression Programming) algorithm based on ORS-GEP (Optimization for RouteSelection based on Gene Expression Programming) algorithm is brought forward in thisthesis. As for the advantages of easy jumping out from local optimal solution of the geneexpression programming, ORS-SAGEP could improve the programming accuracy, and thesimulation results prove its performance.
In conclusion, thesis provides a whole set of IP network traffic monitoring and controlsolution, it describes the establishment of the monitoring model, the network trafficprediction algorithm and the QoS flow control. The solution has been verified the feasibility,and it can play an objective inspiration in actual scene
引文
[1] http://www.cisco.com/en/US/netsol/ns827/networking_solutions_sub_solution.html
[2] Z.Wang and J.Crowcroft. Quality-of-service routing for supporting multimedia applications [J],IEEE Journalon Selected Areas in Communications, Vol14, No:7, Page(s):1228-1234,1996.
[3] A. Juttner, B. Szviatovski, I. Mecs, and Z. Rajko. Lagrange relaxation based method for the QoS routingproblem [C], In proceedings of IEEE INFOCOM2001,Vol2,Page(s):859-868.
[4] S.L. Spitler and D. C. Lee. C [C], In proceedings of IEEE INFOCOM2003, Vol2,Page(s):1446-1455.
[5] Ribeiro M B, Granville L Z,Almeida M.An Architecture Monitor QoS in a Policy-based Network[C].Proc.Of the10th International Conference on Telecommunications,2003.Vol1.Page(s):138-143.
[6] Seising,Rudolf.―Soft concepts‖for Soft Computing in―soft sciences‖on20years of―SoftComputing‖.[C].Fuzzy Systems (FUZZ),2010IEEE International Conference.Page(s):1-8.
[7]郭春生,王盼.基于自组织映射的区域高斯模型的动目标检测[J].中国图象图形学报.2010(15)Page(s):1491-1498.
[8]张富,严丽,马宗民,王星.基于模糊描述逻辑的模糊XML模型的表示与推理[J].计算机学报.2011(08)Page(s):1437-1451.
[9]程经纬,马宗民.模糊描述逻辑知识库查询蕴涵的判定方法[J].计算机学报,2012(04) Page(s):767-785.
[10]邓铁清,任艮全,刘英博.基于遗传算法的工作流个人工作列表资源调度[J].软件学报2012(07)Page(s):1702-1716.
[11]梁亚澜,聂长海.覆盖表生成的遗传算法配置参数优化[J].计算机学报,2012(07) Page(s):1522-153.
[12]徐耀群,孙明,杨树文.混沌神经网络中的超混沌[J].哈尔滨商业大学学报(自然科学版),2006(06)Page(s):54-57.
[13]陈永红,黄席樾.一种混沌系统的设计及混沌序列码的生成方法[J].系统仿真学报.2005(01):199-202.
[14] Oetiker, T. Monitoring your IT gear: the MRTG story[J]. IT Professional2001.3(6) pp.44-48.
[15] Deri,Luca,Chou Ellie.Increasing data center network visibility with cisco NetFlow-Lite[C].Network andService Management (CNSM),20117th.Page(s)1-6.
[16] Rohmad, Mohd Saufy; Azmat, Farok.Enhanced Netflow version9(e-Netflow v9) for network mediation:Structure, experiment and analysis[C].Information Technology,2008.Page(s):1-6
[17] Wang Zhenqi,Wang Xinyu. NetFlow Based Intrusion Detection System[C].MultiMedia and InformationTechnology,2008. MMIT '08. International Conference2008, Page(s):825-828
[18] Haiting Zhu,Xiaoguo Zhang; Wei Ding. Research on Errors of Utilized Bandwidth Measured byNetFlow[C].Networking and Distributed Computing (ICNDC),2011Second International Conference.2011,Page(s):45-49.
[19]董闯.基于硬件探针的网络流量监测研究与实现.[D].北京邮电大学信号与信息处理.2010.
[20] Abellard, A.; Abellard, P.A factorization/defactorization methodology based on data flow petri nets for anefficient hardware/software codesign[C].Systems, Man and Cybernetics,2007. ISIC. IEEE InternationalConference.2007, Page(s):1388-1393.
[21] Yau, S.S.; Chou, C.-R. Control flow analysis of distributed computing system software using structuredPetri net model[C]. Distributed Computing Systems in the1990s,Workshop on the Future Trends ofNetwork.1988:Page(s):174-183.
[22] Li Song, Pascal Bondon, Yang Cao, Qi Cheng. A Time-Varying FARIMA Model for InternetTraffic[C].Proceedings of the2008Congress on Image and Signal Processing, Vol.5.Page(s)83-87.
[23] Stilian Atanasov Stoev. Stable self-similar and locally self-similar random processes: stochastic properties,parameter estimation, and simulation Doctora.[D]Boston University.Jan2005.
[24] C. F. Caiafa. Long correlation Gaussian random fields: Parameter estimation and noise reduction DigitalSignal Processing[D].Jul2007.
[25] Julio C. Ramirez Pacheco, Deni Torres Roman, Leopoldo Estrada Vargas. R/S Statistic: Accuracy andImplementations[C], Proceedings of the18th International Conference on Electronics, Communications andComputers.Page(s):17-22.
[26] Su Zhi Zhang,De Qiang Fan.A New User Search Behavior Forecast Model:ARIMA-SVM Model[C].2010Third International Conference on Education Technology and Training.Volume5.557-560.
[27] Rumelhartd. Learning representations by back propagating errors[J].Nature.1986
[28] Suresh,Sundaram,Omkar,Mani,Vijay P.Parallel implementation of back-propagation algorithm in networksof workstations.[J]Parallel and Distributed Systems.2005,Page(s):24-34.
[29]田妮莉,喻莉.一种基于小波变换和FIR神经网络的广域网网络流量预测模型[J].电子与信息学报.2008(10).Page(s):217-220
[30] ITU-T Recommendation I.371.Traffic Control and Congestion Control in B-ISDN.2000.
[31]孙雁飞,张顺颐,王攀.一种时滞网络自适应主动队列管理算法研究.[J].电子与信息学报2006(10).Page(s):182-187.
[32]陈增强,刘忠信,袁著祉.基于智能预测控制的网络拥塞主动队列管理算法研究[J].智能系统学报.2008(04).Page(s):35-42.
[33] Chan, S.-H.G, Kobayashi.Packet scheduling algorithms and performance of a buffered shufflenet withdeflection routing[J]. Lightwave Technology, Journal of2000.1(4),Page(s):490-501.
[34] Sairam, K,Rao. A packet scheduling algorithm for ad-hoc optical networks[J].Potentials,20062(1).Page(s):30-35.
[35] Polyzos, G.C. A queueing theoretic approach to the delay analysis for the FCFS0.487conflict resolutionalgorithm.[J]. Information Theory, IEEE Transactions on1993.3(6) Page(s):1887-1906.
[36] Jin Xiaohui; Li Jiandong; Guo Feng. Two simple implementation algorithms of WFQ and their performanceanalysis[C]. Info-tech and Info-net,2001. Proceedings. ICII2001-Beijing.2001International Conferences.vol.2.Page(s):526-530.
[37] Joutsensalo, Jyrki; Gomzikov, Oleg.Enhancing revenue maximization with adaptive WRR.[C]Computersand Communication2003. vol.1.Page(s):175-180.
[38]刘君瑞,陈颖图,樊晓桠.基于先到先服务的二维动态优先级信令排队算法[J].计算机科学.2011(05).Page(s):95-98.
[39]钱正德.应用加权公平队列的动态QoS调度架构性能分析[J].上海师范大学学报(自然科学版)2010(06).Page(s):53-59.
[40]牛志升,段翔,刘进.MPLS网络中保证服务质量的多径路由选择策略[J].电子学报2001(12).Page(s):1638-1641.
[41]郑志梅,崔勇.MPLS流量工程最小干扰选路算法研究[J].软件学报2006(04).Page(s):814-821.
[42]冯径,马小骏,顾冠群.适应QoS路由机制的网络模型研究[J].计算机学报.2000(08).Page(s):799-805.
[43]曹雪松,胡瑞敏,王朝萍.覆盖网络中一种公平负载均衡QoS路由算法[J].计算机学报2011(9).Page(s):1650-1659.
[44]林闯,雷蕾.下一代互联网体系结构研究[J].计算机学报.2007(05). Page(s):3-21.
[45]吴建平,吴茜,徐恪.下一代互联网体系结构基础研究及探索[J].计算机学报.2008(09).Page(s):48-60
[46] Mohapatra, S.K. Integrated planning for Next Generation Networks[C].Integrated NetworkManagement-Workshops,2009. IM '09. IFIP/IEEE International Symposium.2009,Page(s):205-210.
[47] Dharwadkar, S.N. Masood.N. Next Generation Network. Consumer Electronics[C],2007.ISCE2007.IEEEInternational Symposium.2007,Page(s):1-4.
[48] Jong Min Lee; Juyoung Park; Shin-Gak Kang; Jun Kyun Choi. Multicast Architecture over Next GenerationNetwork[C]. Advanced Communication Technology,2008. ICACT2008.10th International Conference.2008, Page(s):218-221.
[49] Gufang Tu; Can Zhang; Yi Zhang; Derong Liu. Architecture of Next Generation Network with InformationSharing[C]. Networking, Sensing and Control,2006.Page(s):125-130.
[50]林闯,王元卓,任丰原.新一代网络QoS研究[J].计算机学报.2008(09).pp.37-47.
[51] Menasce, D.A. QoS issues in Web services[J]. Internet Computing, IEEE Volume:6,Issue:6.2002,Page(s):72-75.
[52] Grilo, A.; Macedo, M.; Nunes, M.A scheduling algorithm for QoS support in IEEE802.11networksC.Wireless Communications,2003.Volume:10, Page(s):36-43.
[53] Yuanyuan Li. Study of the monitoring model for securities trading network Quality ofService[C].Information Science and Engineering (ICISE),Page(s):1-4.
[54]叶云.网络演进的业务驱动模式分析[C].中国通信学会信息通信网络技术委员会2005年会. Page(s):9-12
[55] Rikitake, Kenji; Nakao, Koji.NGN and internet: From coexistence to integration.[C]Future Network andServices,2008.Page(s):315-322.
[56]陈运清.城域网组网技术和多业务承载研究[J].电信网技术.2005(04).pp.11-13.
[57] Das, S.K.; Lee, E.; Basu, K.; Sen, S.K.Performance optimization of VoIP calls over wireless links usingH.323protocol[J]. Computers, IEEE Transactions.2003, Page (s):742-752.
[58] Tong Shan; Yang, O.W.W.Bandwidth Management for Supporting Differentiated Service Aware TrafficEngineering[C]. Parallel and Distributed Systems, IEEE Transactions.2007, Page(s):1320-1331.
[59] Goode, B.Voice over Internet protocol (VoIP)[C]. Proceedings of the IEEE.2002,Page(s):1495-1517.
[60] Siangzhee, N.; Achalakul, T.Performance and reliability improvement of the call detail record processingsystem: A case study from a telecommunication enterprise[C].TENCON2009IEEE Region10Conference.Page(s):1-5
[61] Sze, H.P.; Liew, S.C.; Lee, J.Y.B; Yip, D.C.S. A multiplexing scheme for H.323voice-over-IPapplications[J]. Selected Areas in Communications, IEEE Journal.2002,Page(s):1360-1368.
[62] Clark, D.D.; Wenjia Fang. Explicit allocation of best-effort packet delivery service[J]. Networking,IEEE/ACM Transactions.1998,Page(s):362-373.
[63] Lev Buhovsky, Michael Entov, Leonid Polterovich. Poisson brackets and symplectic invariants[J].SelectaMathematica.2012.18(1).
[64] Crouse, M.S.; Nowak, R.D.; Baraniuk, R.G.Wavelet-based statistical signal processing using hiddenMarkov models[J]. Signal Processing, IEEE Transactions.1998, Page(s):886-902.
[65] Kihong Park, Walter Willinger. Self-Similar Network Traffic and Performance Evaluation[M],Wiley,2000.Page(s):94-95.
[66] Heqing Li, Qing Tan. Analysis on Mean Time between Failures Based on Artificial Neural Network[J].Journal of Computers.20127(2).
[67] Zilong, Liu; Guozhong, Liu; Jie, Liu.Adaptive tracking controller using BP neural networks for a class ofnonlinear systems.[J].Systems Engineering and Electronics.2004.Page(s):598-604.
[68]韩敏,王晨,席剑辉．基于改进RBF神经网络的非线性时间序列预测[J].仪器仪表学报2003(24).c579-581
[69] Angeline, P.J., G.M.Saunders, and J.B.Pollack. An evolutionary algorithm that constructs recurrent neuralnetworks [J]. IEEE Transactions on Neural Networks.1993,5:54-65.
[70] Chi-Ho Lee, Jong-Hwan Kim. Evolutionary ordered neural network with a linked-list encoding scheme [C].In proceedings of the1996IEEE International conference on Evolutionary Computation.1996, pages:665-669.
[71] Pujol, J.C.F. and R.Poli. Evolving the topology and the weights of neural networks using a dualrepresentation [J]. Applied Intelligence Journal, Special Issue On Evolutionary Learning.1998,8(1):73-84.
[72] ZHU Yu, ZHANG Hong, KONG Ling-dong. Research of Coal and Gas Outburst Forecasting Based onImmune Genetic Neural Network[C].Second International Workshop on Knowledge Discovery and DataMining, Jan.2009,pages:28-31.
[73] C. FERREIRA. Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (2ndEdition)[M]. Springer, May2006.
[74] Abdollahi, F.; Talebi, H.A.; Patel, R.V. Stable identification of nonlinear systems using neural networks:theory and experiments.Mechatronics[J], IEEE/ASME Transactions.Volume11.Issue:4.2006, Page(s):488-495.
[75]肖道举,毛辉,陈晓苏. BP神经网络在入侵检测中的应用[J]华中科技大学学报(自然科学版)2003.Page(s):518-21.
[76] Nantian Huang.An Improved BP Neural Network Model Based on Quasic-Newton Algorithm[C].NaturalComputation2009.Volume:2.Page(s):352-356
[77] Tom Dayton, Leslie G. Tudor, Robert W.Root.Bellcore's user-centred-design support centre[J].Behaviour&Information Technology.1994.13(1-2).pp.57-66.
[78] Flandrin, P.Wavelet analysis and synthesis of fractional Brownian motion[J].IEEE Trans.InformationTheory.Page(s):1992.910-917.
[79] Ilow, J.Forecasting network traffic using FARIMA models with heavy tailed innovations.Acoustics, Speech,and Signal Processing,2000.Page(s):3814-3817.
[80] Sherif, M. H.; Gregor, R. J.; Lyman, J.Effects of Load on Myoelectric Signals: The ARIMARepresentation.Biomedical Engineering, IEEE Transactions.1981, Page (s):411–416.
[81]崔锦泰.小波分析导论.西安:西安交通大学出版社，1997.
[82] J.H.Lai,P.C.Yuen,G.C.Feng.Face recognition using holistic Fourier invariant features[C].PatternReeognition.2001,34(1):95一09.
[83]蔡念,陈世文,郭文婷,潘晴.融合高斯混合模型和小波变换的运动目标检测.[J].中国图象图形学报.2011(09),Page(s):162-167.
[84]刘维霞,张寅孩,尹涛.基于定子电流小波变换的感应电机速度估计算法的研究.[J].工业控制计算机2010(12), Page(s):65-66+68.
[85]宁辉,陈超.基于小波变换的二相编码信号检测.[J].吉林大学学报(信息科学版)2011(06),Page(s):23-28.
[86]刘嘉焜,金志刚,薛飞.基于FARIMA过程的网络业务预报与应用[J].电子与信息学报2001(04),Page(s):91-95.
[87] MATYAS W，LIANG Y．A Robust Measurement-Based Admission Control with Online TrafficPrediction[J].IEEE COMMUNICATIONS LETTERS.2007.11(2):204-206．
[88] WANG P, LIU Y． Network Traffic Prediction Based on Improved BP Wavelet NeuralNetwork[C]．Proceeding of2008International Conference on Wireless Communications, Networking andMobile Computing. Page(s):1-5．
[89] CHEN D,FENG HH，LIN QJ．Multi-scale Internet Traffic Prediction Using Wavelet Neural NetworkCombined Model[J]. Communications and Networking. Chinacom2006：1-5.
[90]刘岩.网络流量控制若干关键技术研究[D].复旦大学博士学位论文,2004.
[91] S.Saroiu,P.K.Gummadi, and S.D.Gribble. A measurement study of peer-to-peer file sharingsystems[C].Proceedings of Multimedia Computing and Networking (MMCN).January2002,
[92] Schoenen, R.Credit-Based Flow Control for Multihop Wireless Networks and Stochastic Petri NetsAnalysis[C]. Communication Networks and Services Research Conference (CNSR),2011Ninth Annual.2011. Page(s):284-290.
[93] Long, J.; Descotes-Genon, B.Flow optimization method for control synthesis of flexible manufacturingsystems modeled by controlled timed Petri nets[C]. Robotics and Automation,1993. Proceedings.1993IEEEInternational Conference.1993, Page(s):598-603.
[94] Browning, Douglas. Flow control in high-speed communication networks[J].Communications.1994,Page(s):2480-2489.
[95]张娜娜.基于业务感知的认知网络流量控制技术研究.[D].南京邮电大学.信息网络.2011.
[96]邹园萍,糜正琨.基于区分服务感知的MPLS网络流量分配方法.[J].南京邮电大学学报(自然科学版)2007(06).Page(s):27-31.
[97] Gavish B. An algorithm for optimal mute selection in SNA networks[J]. IEEE Transactions onCommunications.1983,3l(10):1154-1161.
[98] Fortz, B.; Thorup, M.Internet traffic engineering by optimizing OSPF weights[C]. Nineteenth Annual JointConference of the IEEE Computer and Communications Societies. Proceedings. IEEE.2000, Page(s):519-528.
[99] Lin, F.Y.S.; Wang, J.L. Minimax open shortest path first routing algorithms in networks supporting theSMDS service[C]. Communications,1993. ICC93. Geneva. Technical Program, Conference Record, IEEEInternational Conference.1993, Page(s):666-670.
[100] Asif, M.; Baig, R.Solving NP-complete problem using ACO algorithm. EmergingTechnologies[C],International Conference.2009, Page(s):13-16.
[101] Beard, R.A.; Lamont, G.B.Determination of Algorithm Parallelism in NP-Complete Problems forDistributed Architectures[C]. Distributed Memory Computing Conference,1990.Page(s):42-51.
[102] Goergen, N.; Liu, K.J.R.; Clancy, T.C.Best-effort cooperative communication without dedicated relays[C].Acoustics Speech and Signal Processing (ICASSP),2010IEEE International Conference.2010, Page(s):3230-3233.
[103] Sridhar Nararsimhan,Hasan Pirkul. Route selection in backbone data communication Networks[J].Computer Networks and ISDN Systems,1988,15(2) Page(s):121-133.
[104]刘润杰,申金媛,穆维新.通信网流量分配方法研究[C].第一届中国高校通信类院系学术研讨会,2007,7Page(s):1066-1072.
[105]申建，许福永.基于禁忌搜索算法的计算机通信网络中容量与流量分配问题韵优化研究[J].兰州大学学报,2003,39(3) Page(s):35-39.
[106]叶大振，吴新余.计算机通信网中路由选择和容量分配的遗传算法求解[J].电子学报,1996,24(12):Page(s):75—78.
[107] C.Ferreira. Gene Expression Programming: A New Adaptive Algorithm for solving Problems [J]. ComplexSystems,2001,13(2) Page(s):87-129.
[108] Zuo Jie, Tang Chang jie, Li Chuan, Yuan Chang-an and Chen An-long. Time Series Prediction based onGene Expression Programming [C]. WAIM04, LNCS, Vol3219,2004, Page(s):55-64.
[109]向勇,唐常杰,曾涛,刘胤田,乔少杰.基于基因表达式编程的多目标优化算法[J].四川大学学报(工程科学版),2007,39(4) Page(s):124-129.
[110] Murai, K.; Hayashi, Y.; Inokuchi, S.; Takaoka, S. A study of optimal target's position in ARPA system.Position Location and Navigation Symposium,2002,Page (s):142-149.
[111] C. FERREIRA. Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (2ndEdition)[M]. Springer, May2006.
[112] Keikha, M.M.Improved Simulated Annealing Using Momentum Terms[C]. Intelligent Systems, Modellingand Simulation (ISMS),2011Second International Conference.2011, Page(s):44-48.
[113] Meijuan Gao; Jingwen Tian. Path Planning for Mobile Robot Based on Improved Simulated AnnealingArtificial Neural Network[C]. Natural Computation,2007. ICNC2007.2007, Page(s):8-12.
[114] Tielin Li; Yamei Yang; Zhibin Liu. An Improved Neural Network Algorithm and Its Application onEnterprise Strategic Management Performance Measurement Based on Kirkpatrick Model[C]. IntelligentInformation Technology Application,2008. IITA '08. Second International Symposium.2008, Page(s):861-865.
[115] http://www.enet.com.cn/cio/atlist0_IPv6%C9%CC%D3%C3.html
[2] Z.Wang and J.Crowcroft. Quality-of-service routing for supporting multimedia applications [J],IEEE Journalon Selected Areas in Communications, Vol14, No:7, Page(s):1228-1234,1996.
[3] A. Juttner, B. Szviatovski, I. Mecs, and Z. Rajko. Lagrange relaxation based method for the QoS routingproblem [C], In proceedings of IEEE INFOCOM2001,Vol2,Page(s):859-868.
[4] S.L. Spitler and D. C. Lee. C [C], In proceedings of IEEE INFOCOM2003, Vol2,Page(s):1446-1455.
[5] Ribeiro M B, Granville L Z,Almeida M.An Architecture Monitor QoS in a Policy-based Network[C].Proc.Of the10th International Conference on Telecommunications,2003.Vol1.Page(s):138-143.
[6] Seising,Rudolf.―Soft concepts‖for Soft Computing in―soft sciences‖on20years of―SoftComputing‖.[C].Fuzzy Systems (FUZZ),2010IEEE International Conference.Page(s):1-8.
[7]郭春生,王盼.基于自组织映射的区域高斯模型的动目标检测[J].中国图象图形学报.2010(15)Page(s):1491-1498.
[8]张富,严丽,马宗民,王星.基于模糊描述逻辑的模糊XML模型的表示与推理[J].计算机学报.2011(08)Page(s):1437-1451.
[9]程经纬,马宗民.模糊描述逻辑知识库查询蕴涵的判定方法[J].计算机学报,2012(04) Page(s):767-785.
[10]邓铁清,任艮全,刘英博.基于遗传算法的工作流个人工作列表资源调度[J].软件学报2012(07)Page(s):1702-1716.
[11]梁亚澜,聂长海.覆盖表生成的遗传算法配置参数优化[J].计算机学报,2012(07) Page(s):1522-153.
[12]徐耀群,孙明,杨树文.混沌神经网络中的超混沌[J].哈尔滨商业大学学报(自然科学版),2006(06)Page(s):54-57.
[13]陈永红,黄席樾.一种混沌系统的设计及混沌序列码的生成方法[J].系统仿真学报.2005(01):199-202.
[14] Oetiker, T. Monitoring your IT gear: the MRTG story[J]. IT Professional2001.3(6) pp.44-48.
[15] Deri,Luca,Chou Ellie.Increasing data center network visibility with cisco NetFlow-Lite[C].Network andService Management (CNSM),20117th.Page(s)1-6.
[16] Rohmad, Mohd Saufy; Azmat, Farok.Enhanced Netflow version9(e-Netflow v9) for network mediation:Structure, experiment and analysis[C].Information Technology,2008.Page(s):1-6
[17] Wang Zhenqi,Wang Xinyu. NetFlow Based Intrusion Detection System[C].MultiMedia and InformationTechnology,2008. MMIT '08. International Conference2008, Page(s):825-828
[18] Haiting Zhu,Xiaoguo Zhang; Wei Ding. Research on Errors of Utilized Bandwidth Measured byNetFlow[C].Networking and Distributed Computing (ICNDC),2011Second International Conference.2011,Page(s):45-49.
[19]董闯.基于硬件探针的网络流量监测研究与实现.[D].北京邮电大学信号与信息处理.2010.
[20] Abellard, A.; Abellard, P.A factorization/defactorization methodology based on data flow petri nets for anefficient hardware/software codesign[C].Systems, Man and Cybernetics,2007. ISIC. IEEE InternationalConference.2007, Page(s):1388-1393.
[21] Yau, S.S.; Chou, C.-R. Control flow analysis of distributed computing system software using structuredPetri net model[C]. Distributed Computing Systems in the1990s,Workshop on the Future Trends ofNetwork.1988:Page(s):174-183.
[22] Li Song, Pascal Bondon, Yang Cao, Qi Cheng. A Time-Varying FARIMA Model for InternetTraffic[C].Proceedings of the2008Congress on Image and Signal Processing, Vol.5.Page(s)83-87.
[23] Stilian Atanasov Stoev. Stable self-similar and locally self-similar random processes: stochastic properties,parameter estimation, and simulation Doctora.[D]Boston University.Jan2005.
[24] C. F. Caiafa. Long correlation Gaussian random fields: Parameter estimation and noise reduction DigitalSignal Processing[D].Jul2007.
[25] Julio C. Ramirez Pacheco, Deni Torres Roman, Leopoldo Estrada Vargas. R/S Statistic: Accuracy andImplementations[C], Proceedings of the18th International Conference on Electronics, Communications andComputers.Page(s):17-22.
[26] Su Zhi Zhang,De Qiang Fan.A New User Search Behavior Forecast Model:ARIMA-SVM Model[C].2010Third International Conference on Education Technology and Training.Volume5.557-560.
[27] Rumelhartd. Learning representations by back propagating errors[J].Nature.1986
[28] Suresh,Sundaram,Omkar,Mani,Vijay P.Parallel implementation of back-propagation algorithm in networksof workstations.[J]Parallel and Distributed Systems.2005,Page(s):24-34.
[29]田妮莉,喻莉.一种基于小波变换和FIR神经网络的广域网网络流量预测模型[J].电子与信息学报.2008(10).Page(s):217-220
[30] ITU-T Recommendation I.371.Traffic Control and Congestion Control in B-ISDN.2000.
[31]孙雁飞,张顺颐,王攀.一种时滞网络自适应主动队列管理算法研究.[J].电子与信息学报2006(10).Page(s):182-187.
[32]陈增强,刘忠信,袁著祉.基于智能预测控制的网络拥塞主动队列管理算法研究[J].智能系统学报.2008(04).Page(s):35-42.
[33] Chan, S.-H.G, Kobayashi.Packet scheduling algorithms and performance of a buffered shufflenet withdeflection routing[J]. Lightwave Technology, Journal of2000.1(4),Page(s):490-501.
[34] Sairam, K,Rao. A packet scheduling algorithm for ad-hoc optical networks[J].Potentials,20062(1).Page(s):30-35.
[35] Polyzos, G.C. A queueing theoretic approach to the delay analysis for the FCFS0.487conflict resolutionalgorithm.[J]. Information Theory, IEEE Transactions on1993.3(6) Page(s):1887-1906.
[36] Jin Xiaohui; Li Jiandong; Guo Feng. Two simple implementation algorithms of WFQ and their performanceanalysis[C]. Info-tech and Info-net,2001. Proceedings. ICII2001-Beijing.2001International Conferences.vol.2.Page(s):526-530.
[37] Joutsensalo, Jyrki; Gomzikov, Oleg.Enhancing revenue maximization with adaptive WRR.[C]Computersand Communication2003. vol.1.Page(s):175-180.
[38]刘君瑞,陈颖图,樊晓桠.基于先到先服务的二维动态优先级信令排队算法[J].计算机科学.2011(05).Page(s):95-98.
[39]钱正德.应用加权公平队列的动态QoS调度架构性能分析[J].上海师范大学学报(自然科学版)2010(06).Page(s):53-59.
[40]牛志升,段翔,刘进.MPLS网络中保证服务质量的多径路由选择策略[J].电子学报2001(12).Page(s):1638-1641.
[41]郑志梅,崔勇.MPLS流量工程最小干扰选路算法研究[J].软件学报2006(04).Page(s):814-821.
[42]冯径,马小骏,顾冠群.适应QoS路由机制的网络模型研究[J].计算机学报.2000(08).Page(s):799-805.
[43]曹雪松,胡瑞敏,王朝萍.覆盖网络中一种公平负载均衡QoS路由算法[J].计算机学报2011(9).Page(s):1650-1659.
[44]林闯,雷蕾.下一代互联网体系结构研究[J].计算机学报.2007(05). Page(s):3-21.
[45]吴建平,吴茜,徐恪.下一代互联网体系结构基础研究及探索[J].计算机学报.2008(09).Page(s):48-60
[46] Mohapatra, S.K. Integrated planning for Next Generation Networks[C].Integrated NetworkManagement-Workshops,2009. IM '09. IFIP/IEEE International Symposium.2009,Page(s):205-210.
[47] Dharwadkar, S.N. Masood.N. Next Generation Network. Consumer Electronics[C],2007.ISCE2007.IEEEInternational Symposium.2007,Page(s):1-4.
[48] Jong Min Lee; Juyoung Park; Shin-Gak Kang; Jun Kyun Choi. Multicast Architecture over Next GenerationNetwork[C]. Advanced Communication Technology,2008. ICACT2008.10th International Conference.2008, Page(s):218-221.
[49] Gufang Tu; Can Zhang; Yi Zhang; Derong Liu. Architecture of Next Generation Network with InformationSharing[C]. Networking, Sensing and Control,2006.Page(s):125-130.
[50]林闯,王元卓,任丰原.新一代网络QoS研究[J].计算机学报.2008(09).pp.37-47.
[51] Menasce, D.A. QoS issues in Web services[J]. Internet Computing, IEEE Volume:6,Issue:6.2002,Page(s):72-75.
[52] Grilo, A.; Macedo, M.; Nunes, M.A scheduling algorithm for QoS support in IEEE802.11networksC.Wireless Communications,2003.Volume:10, Page(s):36-43.
[53] Yuanyuan Li. Study of the monitoring model for securities trading network Quality ofService[C].Information Science and Engineering (ICISE),Page(s):1-4.
[54]叶云.网络演进的业务驱动模式分析[C].中国通信学会信息通信网络技术委员会2005年会. Page(s):9-12
[55] Rikitake, Kenji; Nakao, Koji.NGN and internet: From coexistence to integration.[C]Future Network andServices,2008.Page(s):315-322.
[56]陈运清.城域网组网技术和多业务承载研究[J].电信网技术.2005(04).pp.11-13.
[57] Das, S.K.; Lee, E.; Basu, K.; Sen, S.K.Performance optimization of VoIP calls over wireless links usingH.323protocol[J]. Computers, IEEE Transactions.2003, Page (s):742-752.
[58] Tong Shan; Yang, O.W.W.Bandwidth Management for Supporting Differentiated Service Aware TrafficEngineering[C]. Parallel and Distributed Systems, IEEE Transactions.2007, Page(s):1320-1331.
[59] Goode, B.Voice over Internet protocol (VoIP)[C]. Proceedings of the IEEE.2002,Page(s):1495-1517.
[60] Siangzhee, N.; Achalakul, T.Performance and reliability improvement of the call detail record processingsystem: A case study from a telecommunication enterprise[C].TENCON2009IEEE Region10Conference.Page(s):1-5
[61] Sze, H.P.; Liew, S.C.; Lee, J.Y.B; Yip, D.C.S. A multiplexing scheme for H.323voice-over-IPapplications[J]. Selected Areas in Communications, IEEE Journal.2002,Page(s):1360-1368.
[62] Clark, D.D.; Wenjia Fang. Explicit allocation of best-effort packet delivery service[J]. Networking,IEEE/ACM Transactions.1998,Page(s):362-373.
[63] Lev Buhovsky, Michael Entov, Leonid Polterovich. Poisson brackets and symplectic invariants[J].SelectaMathematica.2012.18(1).
[64] Crouse, M.S.; Nowak, R.D.; Baraniuk, R.G.Wavelet-based statistical signal processing using hiddenMarkov models[J]. Signal Processing, IEEE Transactions.1998, Page(s):886-902.
[65] Kihong Park, Walter Willinger. Self-Similar Network Traffic and Performance Evaluation[M],Wiley,2000.Page(s):94-95.
[66] Heqing Li, Qing Tan. Analysis on Mean Time between Failures Based on Artificial Neural Network[J].Journal of Computers.20127(2).
[67] Zilong, Liu; Guozhong, Liu; Jie, Liu.Adaptive tracking controller using BP neural networks for a class ofnonlinear systems.[J].Systems Engineering and Electronics.2004.Page(s):598-604.
[68]韩敏,王晨,席剑辉．基于改进RBF神经网络的非线性时间序列预测[J].仪器仪表学报2003(24).c579-581
[69] Angeline, P.J., G.M.Saunders, and J.B.Pollack. An evolutionary algorithm that constructs recurrent neuralnetworks [J]. IEEE Transactions on Neural Networks.1993,5:54-65.
[70] Chi-Ho Lee, Jong-Hwan Kim. Evolutionary ordered neural network with a linked-list encoding scheme [C].In proceedings of the1996IEEE International conference on Evolutionary Computation.1996, pages:665-669.
[71] Pujol, J.C.F. and R.Poli. Evolving the topology and the weights of neural networks using a dualrepresentation [J]. Applied Intelligence Journal, Special Issue On Evolutionary Learning.1998,8(1):73-84.
[72] ZHU Yu, ZHANG Hong, KONG Ling-dong. Research of Coal and Gas Outburst Forecasting Based onImmune Genetic Neural Network[C].Second International Workshop on Knowledge Discovery and DataMining, Jan.2009,pages:28-31.
[73] C. FERREIRA. Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (2ndEdition)[M]. Springer, May2006.
[74] Abdollahi, F.; Talebi, H.A.; Patel, R.V. Stable identification of nonlinear systems using neural networks:theory and experiments.Mechatronics[J], IEEE/ASME Transactions.Volume11.Issue:4.2006, Page(s):488-495.
[75]肖道举,毛辉,陈晓苏. BP神经网络在入侵检测中的应用[J]华中科技大学学报(自然科学版)2003.Page(s):518-21.
[76] Nantian Huang.An Improved BP Neural Network Model Based on Quasic-Newton Algorithm[C].NaturalComputation2009.Volume:2.Page(s):352-356
[77] Tom Dayton, Leslie G. Tudor, Robert W.Root.Bellcore's user-centred-design support centre[J].Behaviour&Information Technology.1994.13(1-2).pp.57-66.
[78] Flandrin, P.Wavelet analysis and synthesis of fractional Brownian motion[J].IEEE Trans.InformationTheory.Page(s):1992.910-917.
[79] Ilow, J.Forecasting network traffic using FARIMA models with heavy tailed innovations.Acoustics, Speech,and Signal Processing,2000.Page(s):3814-3817.
[80] Sherif, M. H.; Gregor, R. J.; Lyman, J.Effects of Load on Myoelectric Signals: The ARIMARepresentation.Biomedical Engineering, IEEE Transactions.1981, Page (s):411–416.
[81]崔锦泰.小波分析导论.西安:西安交通大学出版社，1997.
[82] J.H.Lai,P.C.Yuen,G.C.Feng.Face recognition using holistic Fourier invariant features[C].PatternReeognition.2001,34(1):95一09.
[83]蔡念,陈世文,郭文婷,潘晴.融合高斯混合模型和小波变换的运动目标检测.[J].中国图象图形学报.2011(09),Page(s):162-167.
[84]刘维霞,张寅孩,尹涛.基于定子电流小波变换的感应电机速度估计算法的研究.[J].工业控制计算机2010(12), Page(s):65-66+68.
[85]宁辉,陈超.基于小波变换的二相编码信号检测.[J].吉林大学学报(信息科学版)2011(06),Page(s):23-28.
[86]刘嘉焜,金志刚,薛飞.基于FARIMA过程的网络业务预报与应用[J].电子与信息学报2001(04),Page(s):91-95.
[87] MATYAS W，LIANG Y．A Robust Measurement-Based Admission Control with Online TrafficPrediction[J].IEEE COMMUNICATIONS LETTERS.2007.11(2):204-206．
[88] WANG P, LIU Y． Network Traffic Prediction Based on Improved BP Wavelet NeuralNetwork[C]．Proceeding of2008International Conference on Wireless Communications, Networking andMobile Computing. Page(s):1-5．
[89] CHEN D,FENG HH，LIN QJ．Multi-scale Internet Traffic Prediction Using Wavelet Neural NetworkCombined Model[J]. Communications and Networking. Chinacom2006：1-5.
[90]刘岩.网络流量控制若干关键技术研究[D].复旦大学博士学位论文,2004.
[91] S.Saroiu,P.K.Gummadi, and S.D.Gribble. A measurement study of peer-to-peer file sharingsystems[C].Proceedings of Multimedia Computing and Networking (MMCN).January2002,
[92] Schoenen, R.Credit-Based Flow Control for Multihop Wireless Networks and Stochastic Petri NetsAnalysis[C]. Communication Networks and Services Research Conference (CNSR),2011Ninth Annual.2011. Page(s):284-290.
[93] Long, J.; Descotes-Genon, B.Flow optimization method for control synthesis of flexible manufacturingsystems modeled by controlled timed Petri nets[C]. Robotics and Automation,1993. Proceedings.1993IEEEInternational Conference.1993, Page(s):598-603.
[94] Browning, Douglas. Flow control in high-speed communication networks[J].Communications.1994,Page(s):2480-2489.
[95]张娜娜.基于业务感知的认知网络流量控制技术研究.[D].南京邮电大学.信息网络.2011.
[96]邹园萍,糜正琨.基于区分服务感知的MPLS网络流量分配方法.[J].南京邮电大学学报(自然科学版)2007(06).Page(s):27-31.
[97] Gavish B. An algorithm for optimal mute selection in SNA networks[J]. IEEE Transactions onCommunications.1983,3l(10):1154-1161.
[98] Fortz, B.; Thorup, M.Internet traffic engineering by optimizing OSPF weights[C]. Nineteenth Annual JointConference of the IEEE Computer and Communications Societies. Proceedings. IEEE.2000, Page(s):519-528.
[99] Lin, F.Y.S.; Wang, J.L. Minimax open shortest path first routing algorithms in networks supporting theSMDS service[C]. Communications,1993. ICC93. Geneva. Technical Program, Conference Record, IEEEInternational Conference.1993, Page(s):666-670.
[100] Asif, M.; Baig, R.Solving NP-complete problem using ACO algorithm. EmergingTechnologies[C],International Conference.2009, Page(s):13-16.
[101] Beard, R.A.; Lamont, G.B.Determination of Algorithm Parallelism in NP-Complete Problems forDistributed Architectures[C]. Distributed Memory Computing Conference,1990.Page(s):42-51.
[102] Goergen, N.; Liu, K.J.R.; Clancy, T.C.Best-effort cooperative communication without dedicated relays[C].Acoustics Speech and Signal Processing (ICASSP),2010IEEE International Conference.2010, Page(s):3230-3233.
[103] Sridhar Nararsimhan,Hasan Pirkul. Route selection in backbone data communication Networks[J].Computer Networks and ISDN Systems,1988,15(2) Page(s):121-133.
[104]刘润杰,申金媛,穆维新.通信网流量分配方法研究[C].第一届中国高校通信类院系学术研讨会,2007,7Page(s):1066-1072.
[105]申建，许福永.基于禁忌搜索算法的计算机通信网络中容量与流量分配问题韵优化研究[J].兰州大学学报,2003,39(3) Page(s):35-39.
[106]叶大振，吴新余.计算机通信网中路由选择和容量分配的遗传算法求解[J].电子学报,1996,24(12):Page(s):75—78.
[107] C.Ferreira. Gene Expression Programming: A New Adaptive Algorithm for solving Problems [J]. ComplexSystems,2001,13(2) Page(s):87-129.
[108] Zuo Jie, Tang Chang jie, Li Chuan, Yuan Chang-an and Chen An-long. Time Series Prediction based onGene Expression Programming [C]. WAIM04, LNCS, Vol3219,2004, Page(s):55-64.
[109]向勇,唐常杰,曾涛,刘胤田,乔少杰.基于基因表达式编程的多目标优化算法[J].四川大学学报(工程科学版),2007,39(4) Page(s):124-129.
[110] Murai, K.; Hayashi, Y.; Inokuchi, S.; Takaoka, S. A study of optimal target's position in ARPA system.Position Location and Navigation Symposium,2002,Page (s):142-149.
[111] C. FERREIRA. Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (2ndEdition)[M]. Springer, May2006.
[112] Keikha, M.M.Improved Simulated Annealing Using Momentum Terms[C]. Intelligent Systems, Modellingand Simulation (ISMS),2011Second International Conference.2011, Page(s):44-48.
[113] Meijuan Gao; Jingwen Tian. Path Planning for Mobile Robot Based on Improved Simulated AnnealingArtificial Neural Network[C]. Natural Computation,2007. ICNC2007.2007, Page(s):8-12.
[114] Tielin Li; Yamei Yang; Zhibin Liu. An Improved Neural Network Algorithm and Its Application onEnterprise Strategic Management Performance Measurement Based on Kirkpatrick Model[C]. IntelligentInformation Technology Application,2008. IITA '08. Second International Symposium.2008, Page(s):861-865.
[115] http://www.enet.com.cn/cio/atlist0_IPv6%C9%CC%D3%C3.html