用户名: 密码: 验证码:
人工免疫算法在岩土工程中的应用
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
从计算的角度来看,生物免疫系统是一个高度并行、分布、自适应和自组织的系统,具有很强的学习、识别、记忆和特征提取能力。人工免疫系统是对生物免疫系统的模拟,具有强大的信息处理能力,是继人工神经网络、进化计算之后新的智能计算研究领域,是生命科学和计算机科学相互交叉而形成的学科,目前已成为研究热点。
     本文介绍了生物免疫系统、克隆选择原理以及人工免疫系统及其典型应用,对人工免疫算法及其在岩土工程中的应用等方面进行了深入研究,主要包括下以内容:
     (1)介绍了生物免疫系统的一些基础概念、功能和原理;分析了遗传算法早熟收敛的成因、人工免疫算法的基本理论以及常用免疫算法的基本结构和流程。用5个标准测试函数对克隆选择算法、遗传算法的收敛性能进行了测试,结果表明克隆选择算法在不同类型的函数上具有较快的收敛速度和较高的收敛精度。
     (2)介绍了可靠度理论的基础知识,基于免疫算法原理和可靠指标的几何涵义,提出了计算岩土工程可靠指标和设计验算点的全局优化算法。对于功能函数的非线性和复杂性,避免了繁复的求导数工作。通过两个工程实例,证明了提出的方法进行岩土工程可靠度分析的有效性。
     (3)结合武汉地区混凝土管桩试桩资料进行了统计学分析和可靠度分析。采用了JC法和免疫算法两种方法进行可靠度指标的计算。在求解过程中,对于功能函数的复杂性,免疫算法仅需要目标函数的函数值。概括了多元复合地基承载力计算方法,并推导出多元复合地基可靠度研究中的极限承载力状态方程。利用MATLAB编制了相应的计算程序。通过算例,采用Monte-Carlo法和免疫算法进行对比计算,结果表明免疫算法在进行多元复合地基承载力的可靠度分析时,收敛速度快于Monte-Carlo法并且结果精度高。
     (4)单桩极限承载力受众多因素的影响,Q—S曲线表现出复杂的非线性特征。结合武汉地区预应力混凝土管桩静载荷试验资料,运用MATLAB编写了免疫算法程序对预应力混凝土管桩的极限承载力进行了预测分析。计算结果与试验资料基本一致。
     (5)沉降预测是岩土工程研究领域一个重要课题,也是工程设计阶段值得关心的问题。应用免疫算法对沉降进行预测,并与最小二乘法、Asaoka法和遗传算法的预测结果进行比较。结果表明,免疫算法是进行沉降预测的有效方法。
From the information-processing perspective, the immune system is a highly parallel and distributed intelligent system that has learning, recognition, memory, and associative retrieval capabilities. Artificial Immune System, which has powerful information processing ability, simulates Biology Immune System. It is a novel intelligent computing research field following the invention of Artificial Neural Network and Evolutionary Computation, and it is an emergent interdisciplinary research field generated by life science and computer science and has become a hot point.
     The basic principles of the biologic immune system, the Clonal Selection Priciple, the researches and typical applications of AIS are introduced in this dissertation. The immune algorithm and its applications in geotechnical engineering are studied. The main works of this dissertation are summarized as follows.
     (1) Some basic concepts, functions and principles of the biological immune system are introduced. Then the causes of the premature convergence of the genetic algorithm (GA), the basic theory of IA, structure and process of the IA are analyzed. To verify the excellence of the immune algorithm, five numerical objective functions are adopted to compare the performance of genetic algorithm and immune algorithm. The simulation results demonstrate that IA has faster convergence speed and higher convergence accuracy.
     (2) The basic concepts of reliability theory are introduced. Based on the immune algorithm and geometric implication of the reliability index, a global optimization method is put forward to calculate the reliability index. By this method, reliability of the nonlinear and complex performance function of geotechnical engineering can be obtained without derivation. Two practical examples show that the method presented in this dissertation is reliable and accurate in the reliability analysis of geotechnical engineering.
     (3) Based on the results of static load tests of bored piles in Wuhan area, the statistics and reliability analyses of the bearing capacity of single PC pile are performed by utilizing the limit state equation of dimensionless random variables. The index of reliability of the single PC pile is calculated with both IA method and JC method. By immune algorithm, only the objective function value is used, reliability of the nonlinear and complex performance function of geotechnical engineering can be obtained without derivation. In recently years, multi-column composite foundation is widely used. The classification and the computation methods of bearing capacity of multi-column composite ground are introduced, and the ultimate bearing capacity equation is deduced. The program of computing reliability index is developed in MATLAB. Three practical examples using Monte-Carlo method and immune algorithm show that immune algorithm has the advantages of rapid convergence and high precision in the reliability analysis of bearing capacity of multi-column composite ground.
     (4) The Q-S curve of single pile has complicated nonlinear features because the ultimate bearing capacity of single pile is affected by many factors. Based on the results of static load test of prestressed concrete pipe piles in Wuhan area, immune algorithm program is developed by MATLAB to predict the ultimate bearing capacity of prestressed concrete pipe piles. Calculated results are in agreement with those from measurement.
     (5) To predict the settlement of foundations is an important issue in geotechnical engineering and one of the main concerns in design. IA is used in an attempt to obtain accurate settlement prediction. The predicted settlements obtained by IA are compared with those predicted by the least squares fitting method, Asaoka method and GA. The results show that IA is a useful technique for predicting the settlement of foundations.
引文
[1]蔡自兴,徐光祐.人工智能及其应用.北京:清华大学出版社,2003
    [2]徐宗本,张讲社,郑亚林.计算智能中的仿生学:理论与算法.北京:科学出版社,2003
    [3]靳蕃.神经计算智能基础·原理·方法.成都:西南交通大学出版,2000
    [4]Ackley D H,Hinton G E,Sejnowski T J.A lesrning algorithm for Boltzmann machines.Cognitive Science,1985,(9):147-169
    [5]陈仁.免疫学基础.北京:人民卫生出版社,1982
    [6]漆安慎,杜婵英.免疫的非线性模型.上海:上海科技教育出版社,1999
    [7]Dasgupta D.An overview of artificial immune systems and their applications.In:Artificial Immune Systems and Their Applications.Berlin Germany:Springer-Verlag,1998:3-18
    [8]焦李成,杜海峰,刘 芳等.免疫优化计算、学习与识别.北京:科学出版社,2006
    [9]李涛.计算机免疫学.北京:电子工业出版社,2004
    [10]莫宏伟.人工免疫系统原理与应用.哈尔滨:哈尔滨工业大学出版社,2003
    [11]陈慰峰.医学免疫学.北京:人民卫生出版社,2001
    [12]Lyclyard P M,Whelan A,Fanger M W.Instant Notes in Immunology.UK:BIOS ScientificPub.Ltd,2000
    [13]张卓然.医学微生物学和免疫学(第四版).北京:人民卫生出版社,2000
    [14]丁永生.计算智能--理论、技术与应用.北京:科学出版社,2004
    [15]吴敏毓,刘恭植.医学免疫学(第四版).合肥:中国科学技术大学出版社,1993
    [16]Hebb D O.The Organization of Behavior.New York:Wiley,1949
    [17]Hopfield J J.Neural networks and physical system with emergent collective computation abilities.Proceedings of the National Academy of Science(USA),1982,79:2554-2558
    [18]Kohonen T.Self-Organization and Associative Memory(2~(nd) Edition).Berlin:Spring-Verlag,1987
    [19]周 明,孙树栋.遗传算法原理及应用.北京:国防工业出版社,1999
    [20]陈国良,王煦法,庄镇泉等.遗传算法及其应用.北京:人民邮电出版社,1996
    [21]Dasgupta D.Artificial Immune Systems and their Applications(1~(st) Edition).New York:Springer-Verlag,1998
    [22]de Castro L N,Timmis J.Artificial Immune Systems:A New Computational Intelligence Approach.London:Springer-Verlag,2002
    [23]Tarakanov A,Dasgupta D.A formal model of an artificial immune system.Biosystems,2000,55(1):151-158
    [24]Farmer J D,Packard N H,Perelson A S.The Immune System,Adaptation,and Machine Learning.Physica D,1986,22:187-204
    [25]Bersini H,Varela F J.The immune recruitment mechanism:a selective evolutionary stratege.In:Artificial Immune Systems and Their Applications.San Mateo Calif:Morgan Kauffman Publishers,1991:520-526
    [26]Smith R E,Forrest S,Perelson A S.Searching for diverse,cooperative population with genetic algorithms.Evolutionary Computation,1993,1(2):127-149
    [27]Mori K,Tsukiyama M,Fukuda T.Immune algorithm with searching diversity and its application to resource allocation problem.The Trans.of Institute of Electrical Engineering of Japan,1993,113-C(10):872-878
    [28]Jerne N K.The immune system.Scientific American,1973,229(1):52-60
    [29]Jerne N K.Towards a network theory of the immune system.Annual Immunology,1974,125c:373-389
    [30]Farmer J D.A Rosetta stone for connectionism.Physica,1990,42(D):153-187
    [31]Perelson A S.Immune network theory.Immunological Reviews,1989,(110):5-36
    [32]de Castro L N,von Zuben F J.The clone selection algorithm with engineering applications.In:Proceedings of Genetic and Evolutionary Computation Conference.Las Vegas,2000:36-37
    [33]de Castro L N,yon Zuben F J.Learning and optimization using the clonal selection principle.IEEE Transaction on Evolutionary Computation,2002,6(3):239-251
    [34]de Castro L N,Timmis J.An artificial immune network for multimodal function optimization.In:Proceedings of IEEE Congress on Evolutionary Computation.Hawaii,2002:699-704
    [35]Coello C A C,Cortes N C.An approach to solve multiobjective optimization problems based on artificial immune system.In:1st International Conference on Artificial Immune Systems.Canterbury,UK,2002:212-221
    [36]Coello C A C,Cortes N C.Solving multiobjective optimization problems using an artificial immune system.Genetic Programming and Evolvable Machines,2005,6(2):163-190
    [37]Wierzchon S T.Function Optimization by the immune metaphor.TASK QUARTERLY,2002,6(3):1-16
    [38]Bersini H.The immune and the chemical crossover.Evolutionary Computation,2002,6(3):306-313
    [39]王磊,潘进,焦李成.免疫规划.计算机学报,2000,23(8):806-812
    [40]Wang L,Jiao L.A novel genetic algorithm based on immunity.IEEE Transaction on System,Man,And Cybernetics -Part A:Systems and Humans,2000,30(5):552-561
    [41]王煦法,张显俊,曹先彬.一种基于免疫原理的遗传算法.小型微型计算机系统,1999,20(2):17-20
    [42]凌军,曹 阳,尹建华等.基于小生境技术的多样性抗体生成算法.电子学报,2003,31(8):1130-1133
    [43]高 洁.应用免疫算法进行电网规划研究.系统工程理论与实践,2001,(5):119-123
    [44]Mori K,Tsukiyama M,Fukuda T.Application of an immune algorithm to multi-optimization problems.Electrical Engineering IN Japan,1998,122(2):30-37
    [45]孙勇智,韦巍.基于人工免疫算法的电力系统最优潮流计算.电力系统自动化,2002,26(12):30-34
    [46]Chun J,Lim J,Jung H,et al.Optimal design of synchronous motor with parameter correction using immune algorithm.IEEE Transaction on Energy Conversion,1999,14(3):610-615
    [47]Endoh S,Toma N,Yamada K.Immune algorithm for N-Tsp.In:IEEE International Conference on System,Man and Cyernetics.San Diego,California,USA,1998:3844-3849
    [48]曹先彬,刘克胜,王阳法.基于免疫遗传算法的装箱问题.2000,21(4):361-363
    [49]Lin C H,Chen C S,Wu C J,et al.Application of immune algorithm to optimal dwitching operation for distribution-loss minimisation and loading balance.IEEE Proceeding of Generation,Transmission and Distribution,2003,150(2):183-189
    [50]李 蔚,刘长东,盛德仁等.基于免疫算法的机组负荷优化分配研究.中国电机工程学报,2004,24(7):241-245
    [51]Mori K,Tsukiyama M,Fukuda T.Adaptive scheduling system inspired by immune System.In:IEEE Internation Conference on System,Man,and Cybernetics.San Diego,California,1998:3833-3837
    [52]Tazawa I,Koakutsu S,Hirata H.Evolutionary optimization based on the immune system and its application to the vlsi floor-plan design problem.Electrical Engineering,1998,124(4):27-36
    [53]Forrest S,Hofmeyr S A,Somayaji A.Computer immunology.Communications of the ACM,1997,40(10):88-96
    [54]Okamoto T,Ishida Y.A distributed approach against computer viruses inspired by the immune system.IEICE Transactions on Communications,2000,E83-B(5):908-915
    [55]Liang Y,Li H,long L,et al.A multi-agent immune model for security computer.Wuhan University Journal of Natural Sciences,2001,6(1-2):486-490
    [56]王煦法,曹先彬,张四海.基于免疫识别的免疫算法.电子学报,2002,20(12):1840-1844
    [57]Kim J,Bentley P J.Towards an artificial immune system for network intrusion detection:an investigation of dynamic elonal selection.In:Proceeding of the 2001Congress on Evolutionary Computation.Seoul,Korea:IEEE Computer Society,2001:1015-1020
    [58]Dasgupta D,Cao Y,Yang C.An immunogenetic approach to spectra recognition.In:Genetic and Evolutionary Computation Conference.San Francisco,USA,1999:149-155
    [59]Hunt J E,Cooke D E.An adaptive,distributed learning system based on the immune system..In:IEEE International Conference on Systems,Man and Cybernetics.Vancouver,Canada,1995:2494-2499
    [60]Ishida Y,Adachi N.An immune algorithm for multiagent:application to adaptive noiseneutralization.In:Proceedings of the 1996 International Conference on Intelligent Robots and Systems.Osaka,Japan,1996a:1739-1746
    [61]Ishida Y,Adachi N.Active noise control by an immune algorithm:application in immune system as an evolution.In:Proceedings of IEEE Internation Conference on Evolutionary Computation 1996.Nagoya,Japan,1996b:150-153
    [62]Lee D,Sim K.Artificial immune network-based cooperative control in collective autonomous mobile robots.In:Proceeding 6th IEEE Internation Workshop on Robot and Human Communication.Sendai,Japan,1997:58-63
    [63]Takahashi K,Yamada T.Application of an immune feedback mechanism to control systems.JSME International Journal,1998,41(2):184-191
    [64]Dasgupta D,Forrest S.Artificial immune systems in industrial applications.In:Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials.Honolulu,1999:257-267
    [65]Bradley D W,Tyrrell A M.Hardware fault tolerance:an immunological solution.In:IEEE International Conference on Systems,Man,and Cybernetics.Nashville,USA,2000:107-112
    [66]Gibert C J,Routen T W.Associative memory in an immune-based system.In:Proceedings of the twelfth national conference on Artificial intelligence.Seattle,USA,1994:852-857
    [67]Abbattista F,di Santo G,di Santo G,et al.An associative memory based on the immune networks.In:IEEE International Conference on Neural Networks 1996.Washington,USA,1996:519-523
    [68]Ishiguro A,Watanabe Y,Kondo T,et al.A robot with a decentralized consensus-making mechanism based on the immune system.In:Proceedings of the 3rd International Symposium on Autonomous Decentralized Systems.Berlin,Germany,1997:231-237
    [69]Hunt J E,Cooke D E,Holstein H.Case memory and retrieval based on the immune system.In:Proceedings of the First International Conference on Case-Based Reasoning Research and Development.London,1995:205-216
    [70]袁亚湘,孙文瑜.最优化理论与方法.北京:科学出版社,1997
    [71]王凌.智能优化算法及其应用.北京:清华大学出版社,2001
    [72]Holland J H.Adaptation in Natural and Artificial System.MI:Univ.Michigan Press,1975
    [73]雷英杰,张善文,李续武等.MATLAB遗传算法工具箱及应用.西安:西安电子科技大学出版社,2005
    [74]林焰,郝聚民.隔离小生境遗传算法研究.系统工程学报,2000,15(1):86-91
    [75]Chun J S,Kim M K,Jung H K,et al.Shape optimization of electromagnetic devices using immune algorithm.IEEE Transactions on Magnetics,1997,33(2):1876-1879
    [76]Tasswa I,Koakusu S,Hirata H.An evolutionary optimization based on the immune system and its application to the vlal floor plan design problem.Electrical engineering,1998,122(2):30-37
    [77]Timmis J,Edmonds C,Kelsey J.Assessing the performance of two immune inspired algorithms and a hybrid genetic algorithm for function optimisation.Congress on Evolutionary Computation,2004,1(19-23):1044-1051
    [78]Oprea M,Forrest S.How the immune system generates diversity:pathogen space coverage with random and evolved antibody libraries.In:Genetic and Evolutionary Computation Conference.1999:1651-1656
    [79]葛 红,毛宗源.免疫算法的改进.华南理工大学学报(自然科学版),2002,30(12):15-18
    [80]焦李成,杜海峰.人工免疫系统进展与展望.电子学报,2003,91(10):1540-1548
    [81]Meshref H,VanLandingham H.Artificial immune systems:application to autonomous agents.2000 IEEE International Conference on Systems,Man,and Cybernetics,2000,1(1):61-66
    [82]罗印升,李人厚,张雷等.人工免疫算法在函数优化中的应用.西安交通大学学报,2003,37(8):840-843
    [83]Rudolph J G.Convergence analysis of canonical genetic algorithm.IEEE Trans.on Neural Network,1994,5(1):96-101
    [84]Qi X F,Palmieri F.Theoretical analysis of evolutionary algorithms with an infinitepopulation size in continuous space.Part Ⅰ:Basic properties of selection and mutation.IEEE Transaction on Neural Network,1994,5(1):102-119
    [85]于瀛,候朝桢.一种克隆选择算法的收敛性分析.计算机应用研究,2006,(6):96-98
    [86]孙勇智.人工免疫系统模型、算法及其应用研究[博士学位论文].杭州:浙江大学,2004
    [87]吕 岗.免疫算法及其应用研究[博士学位论文].徐州:中国矿业大学,2003
    [88]罗小平,韦巍.生物免疫遗传算法的几乎处处强收敛性分析及收敛速度估计.电子学报,2005,33(10):1803-1807
    [89]赵国藩.工程结构可靠性理论与应用.大连:大连理工大学出版社,1996
    [90]工程结构可靠度设计统一标准(GB 50153-92).北京:中国建筑工业出版社,1992
    [91]Hasofer A M,Lind N C.Exact and invariant second-moment code format.Journal of Engineering Mechanics.ASCE,1974,100(1):111-121
    [92]赵衍刚,汪近仁.一个以遗传算法为基础的结构可靠度分析方法.地震工程与工程振动,1995,15(3):47-58
    [93]吴世伟.结构可靠度分析.北京:人民交通出版社,1990
    [94]桂劲松,康海贵.结构可靠度分析的响应面法及MATLAB实现.计算力学,2004,21(12):683-687
    [95]冷伍明.基础工程可靠度分析与设计理论.长沙:中南大学出版杜,2000
    [96]郑俊杰,刘志刚.石灰桩与深层搅拌桩联合加固杂填土.施工技术,1997,(9):23-24
    [97]郑俊杰,袁内镇.石灰桩与深层搅拌桩联合加固深厚软土.岩土工程技术,1999,(2):33-34
    [98]郑俊杰,张建平.CFG桩与石灰桩联合处理不均匀地基.施工技术,2000,(9):31-32
    [99]郑俊杰,区剑华,吴世明等.多元复合地基的理论与实践.岩土工程学报,2002,24(2):208-212
    [100]龚晓南.复合地基理论及工程应用.北京:中国建筑工业出版社,2002
    [101]吕福庆,吴文.桩的垂直静载试验极限承载力判定方法综述.岩土力学,1995,16(2):86-93
    [102]建筑桩基技术规范(JGJ 94-2008).北京:中国建筑工业出版社,2008
    [103]徐攸在,刘兴满.桩的动测新技术.北京:中国建筑工业出版社,1989
    [104]林宗元.岩土工程试验监测手册.沈阳:辽宁科学技术出版社,1994
    [105]基桩低应变动力检测规程(JGJ/T 93-95).北京:中国建筑工业出版社,1995
    [106]冷曦晨.大型桥梁桩基承载力试验研究[博士学位论文].北京:中国地质大学,2005
    [107]温特科恩著,方晓阳译.基础工程手册.北京:中国建筑工业出版社,1983
    [108]李广信.高等土力学.北京:清华大学出版社,2004
    [109]折学森.软土地基沉降计算.北京:人民交通出版社,1998
    [110]曾国熙.砂井地基沉陷分析.浙江大学学报,1959,(3):34-72
    [111]《地基处理手册》编委会.地基处理手册.北京:中国建筑工业出版社,1998
    [112]魏汝龙.从实测沉降推算固结系数.岩土工程学报,1993,15(2):15-21
    [113]杨 涛,李国维,杨伟清.基于双曲线法的分级填筑路堤沉降预测.岩土力学,2004,25(10):1551-1554
    [114]Asaoka A.Observational procedure of settlement prediction.Soils & Foundations,1978,18(4):87-101
    [115]邓聚龙.灰色控制系统.武汉:华中理工大学出版社,1988
    [116]朱杰,孙树林.灰色模型在软土路基沉降预测中的应用.路基工程,2006,(4):84-87
    [117]张仪萍,俞亚南.沉降预测中的灰色模型理论与Asaoka法.系统工程理论与实践,2002,(9):18-24
    [118]胡中雄.土力学和环境土工学.上海:同济大学出版社,1997
    [119]冯文凯,刘汉超.修正双曲线法在路基沉降变形初期阶段的应用探讨.地质灾害与环境保护,2001,12(3):60-63
    [120]吴心怡.高等级公路路堤沉降计算方法研究[硕士学位论文].南京:河海大学,1995
    [121]宰金珉,梅国雄.全过程的沉降量预测方法研究.岩土力学,2000,21(4):322-325
    [122]李德春.生长曲线在土坝沉陷分析中的应用.大坝观测与土工测试,1991,15(2):28-30
    [123]梅国雄,宰金珉,殷宗泽等.沉降-时间曲线呈“S”型的证明--从一维固结理论角度.岩土力学,2004,25(1):20-22
    [124]宋彦辉,聂德新.基础沉降预测的Verhulst模型.岩土力学,2003,24(1):123-126
    [125]吴雄伟,潘海平.灰色Verhulst模型在路堤沉降预测中的应用.浙江水利科技,2001,(6):28-32
    [126]许永明,徐泽中.一种预测路基工后沉降量的方法.河海大学学报,2000,28(5):111-113
    [127]王志亮,黄景忠,李永池.沉降预测中的Asaoka法应用研究.岩土力学,2006,27(11):2025-2028
    [128]张仪萍,张土乔,龚晓南.沉降的灰色预测.工业建筑,1999,29(4):45-48
    [129]吴大志,李夕兵,蒋卫东.灰色理论在高路堤沉降预测中的应用.中南工业大学学报,2002,33(3):230-233
    [130]魏迎奇,张海霞.基础沉降的灰色预测模型.河海大学学报,1998,26(5):107-109
    [131]凌迎春.GM(1,1)置零建模法及其应用.系统工程理论与实践,1996,16(5):108-112
    [132]东南大学交通学院.宁杭高速公路溧阳段四、五标沉降观测汇报资料.南京:东南大学,2002
    [133]张丽华,蔡美峰,牛庆莲.复合地基全过程沉降预测的威布尔模型.工业建筑,2006,36(10):54-56

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700