高层建筑结构智能型式优化的现状与趋势
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摘要
系统地分析了基于专家系统、实例推理与知识发现的高层结构智能型式优化方法的研究现状,指出了每种方法的特征与不足;预测了集成智能型式优化方法将是型式优化的重要发展方向;给出了4种集成智能型式优化方法,并建立了融合利用ES、CBR、KDD与智能算法的集成智能型式优化系统模型,该模型综合应用了专家智能、机器智能与计算智能,较好地模拟了领域专家在解决结构型式优化问题时的复杂思维过程,实现了其所用知识、方法、策略与手段的统一.为深入研究结构智能型式优化理论与方法,减小结构型式优化盲目性及风险性等将有重要的理论和实用价值.
The present research state of structural intelligent form optimization methods of high-rise buildings which are based on ES,CBR,KDD are introduced systematically and the characteristics and deficiency of each method are also pointed out. Then,it is predicted that the integral intelligent form optimization method will be an important development direction.At last,four intelligent form optimization methods are given and a integral intelligent form selection model using ES,CBR,KDD and intelligent arithmetic is set up.The model,which utilizes expert aptitude,machine aptitude and compute aptitude,has effectively simulated the complex process of domain expert resolving intelligent form optimization problems and realized the integration of knowledge,means,maneuver and artifice.The model will play an important theoretical and practical value in deeply studying the theory and technique of structural intelligent form optimization and reducing the blindness and risk of structural intelligent form optimization.
The present research state of structural intelligent form optimization methods of high-rise buildings which are based on ES,CBR,KDD are introduced systematically and the characteristics and deficiency of each method are also pointed out. Then,it is predicted that the integral intelligent form optimization method will be an important development direction.At last,four intelligent form optimization methods are given and a integral intelligent form selection model using ES,CBR,KDD and intelligent arithmetic is set up.The model,which utilizes expert aptitude,machine aptitude and compute aptitude,has effectively simulated the complex process of domain expert resolving intelligent form optimization problems and realized the integration of knowledge,means,maneuver and artifice.The model will play an important theoretical and practical value in deeply studying the theory and technique of structural intelligent form optimization and reducing the blindness and risk of structural intelligent form optimization.
引文
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[18]吕大刚,张世海,王光远.结构选型智能决策支持系统的总体设计及关键技术研究[A].国家自然科学基金“九五”重大项目“大型复杂结构的关键科学问题及设计理论研究”论文集[C].大连:大连理工大学出版社,2000.325-332.
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[21]SCHANK R.Dynam ic M emory:A Theory of Rem in-d ing and Learn ing in Computers and Peop le[M].Cam-bridge:Cambridge Un iversity Press,1982.
[22]VENKATAMARAN S,KR ISHNAN R,RAO K.A rule-case based system for image analysis[A].First EuropeanWorkshop on Case Based Reasoning,Posters and Presenta-tions[C].[s.l.]:University ofKaiserslautern,1993.
[23]OKAMOTO S,SATOH K.An average-case analysisof k-nearest ne ighbor c lassifier[A].ICCBR’95[C].[s.l.]:[s.n.],1995.253-264.
[24]史忠植.高级人工智能[M].北京:科学出版社,1998.78-179.
[25]李楚舒,刘西拉.基于事例的设计推理[J].工程设计CAD与智能建筑,1999(1):41-43.
[26]陆汝铃.世纪之交的知识工程与知识科学[M].北京:清华大学出版社,2001.
[27]LEAKE D.Case-Based Reasoning:Experiences,Les-sons,and Future D irections[M].Menlo Park:AAAIPress,1996.
[28]AMODT A,PLAZA E.Case-based reasoning:Founda-tional issues,methodological variations and system approa-ches[J].AI Communications,1994,7(1):39-59.
[29]GERO J S.AI in Design’92[M].[s.l.]:K luwerAc-adem ic Pub lishers,1992.
[30]FALTINGS,HUA K.Case-based representation of ar-ch itectural design know ledge[A].Proceed ings of theDARPA W orkshop on Case-Based Reason ing[C].W ash ington D C:[s.n.],1991.307-316.
[31]SO IBELMAN L,PENA-MORA F.D istributed mu lti-reason ing m echan ism to support conceptual structuraldesign[J].Journal of Structural Engineering,2000,126(6):28-32.
[32]LI C S,LIU X L,DONG C.Case-based reasoning in struc-tural prelim inary design for high-rise buildings[A].Pro-ceedings ICAIE’98[C].[s.l.]:[s.n.],1998.
[33]邢方亮,王光远.基于SOFM实例推理系统的结构选型[J].工程力学,2003,20(1):1-6.
[34]ZHANG Sh ihai,LIU X iaoyan,OU Jinp ing,et al.CBR,KDD and sm art algorism s based design m ethodsfor h igh-rise structure form-selection[J].Pac ificSc ience Review,2002,4:30-35.
[35]张世海.高层建筑结构智能选型的理论与方法研究[D].哈尔滨:哈尔滨工业大学,2003.
[36]FAN Jianua.An overview of data m in ing and know l-edge d iscovery[J].Comput Sc i&Technol,1998,13(4):348-368.
[37]王光远,张世海.高层建筑结构方案实例库系统及其在结构智能选型中应用[J].工程力学,2003,20(4):1-7.
[2]蔡自兴,徐光佑.人工智能及其应用[M].北京:清华大学出版社,1996.18-25.
[3]GERO J S.Knowledge Engineering in Computer-aided De-sign[M].Amsterdam:Elesevier Science Publishers,1985.
[4]MAHER M L.Expert systems for structural design[J].Computing in C ivil Engrg,ASCE,1987,1(4):270-283.
[5]SABOUNI A R,AI-MOURAD O M.Quantitativeknow ledge based approach for prelim inary design of tallbu ild ings[J].Artific ial Intelligence in Engineering,1997,11:143-154.
[6]SO IBELMAN L.The exp loration of an integrated repre-sentation for the conceptual design phase of structuraldesign for tall bu ild ings through d istributed mu lti-rea-son ing algorithm s[D].Cambridge:M assachusetts Insti-tute of Technology,1998.
[7]SO IBELMAN L,PENA-MORA F.D istributed mu lti-reason ing m echan ism to support conceptual structuraldesign[J].Journal of Structural Engineering,2000,126(6):733-742.
[8]张瑾.基于神经网络的高层建筑结构初步设计专家系统(H IDE-Ⅰ)[D].北京:清华大学,1989.
[9]何广乾.高层建筑结构初步设计专家系统课题总结[R].北京:中国建筑科学研究院,1991.
[10]陆为民,扬建华.多高层钢筋砼房屋抗震初步设计专家系统[J].工程力学,1991,8(4):80-87.
[11]曲宏,陆为民.高层混凝土建筑的抗震选型支持系统[J].同济大学学报,1995,23(2):293-302.
[12]张世海.高层钢筋砼结构抗震选型及其专家系统[D].哈尔滨:哈尔滨工业大学,1996.
[13]欧进萍,张世海.高层钢筋混凝土结构抗震选型的模糊专家系统[J].地震工程与工程振动,1997,17(2):82-91.
[14]赖明,扬溥.钢筋混凝土抗震结构选型的模糊综合评判[J].建筑结构学报,1996,17(8):44-51.
[15]谭克艰,曹晖,毛沂.建筑体型抗震性能模糊评判专家系统[J].重庆建筑大学学报,1997,19(6):108-112.
[16]刘希拉,甘明.基于神经网络的结构初步设计专家系统[J].清华大学学报(自然科学版),1995(S3):56-61.
[17]刘希拉,李楚舒.基于神经网络的高层结构体系选择[J].建筑结构学报,1999,20(5):36-41.
[18]吕大刚,张世海,王光远.结构选型智能决策支持系统的总体设计及关键技术研究[A].国家自然科学基金“九五”重大项目“大型复杂结构的关键科学问题及设计理论研究”论文集[C].大连:大连理工大学出版社,2000.325-332.
[19]张世海.高层建筑基础方案优选过程及决策方法研究[A].第八界高层建筑抗震技术交流会论文集[C].[s.l.]:[s.n.],2001.199-206.
[20]邢方亮,张世海,王光远.结构选型中基于模糊推理的评判系统[J].工程力学,2002,19(5):12-15.
[21]SCHANK R.Dynam ic M emory:A Theory of Rem in-d ing and Learn ing in Computers and Peop le[M].Cam-bridge:Cambridge Un iversity Press,1982.
[22]VENKATAMARAN S,KR ISHNAN R,RAO K.A rule-case based system for image analysis[A].First EuropeanWorkshop on Case Based Reasoning,Posters and Presenta-tions[C].[s.l.]:University ofKaiserslautern,1993.
[23]OKAMOTO S,SATOH K.An average-case analysisof k-nearest ne ighbor c lassifier[A].ICCBR’95[C].[s.l.]:[s.n.],1995.253-264.
[24]史忠植.高级人工智能[M].北京:科学出版社,1998.78-179.
[25]李楚舒,刘西拉.基于事例的设计推理[J].工程设计CAD与智能建筑,1999(1):41-43.
[26]陆汝铃.世纪之交的知识工程与知识科学[M].北京:清华大学出版社,2001.
[27]LEAKE D.Case-Based Reasoning:Experiences,Les-sons,and Future D irections[M].Menlo Park:AAAIPress,1996.
[28]AMODT A,PLAZA E.Case-based reasoning:Founda-tional issues,methodological variations and system approa-ches[J].AI Communications,1994,7(1):39-59.
[29]GERO J S.AI in Design’92[M].[s.l.]:K luwerAc-adem ic Pub lishers,1992.
[30]FALTINGS,HUA K.Case-based representation of ar-ch itectural design know ledge[A].Proceed ings of theDARPA W orkshop on Case-Based Reason ing[C].W ash ington D C:[s.n.],1991.307-316.
[31]SO IBELMAN L,PENA-MORA F.D istributed mu lti-reason ing m echan ism to support conceptual structuraldesign[J].Journal of Structural Engineering,2000,126(6):28-32.
[32]LI C S,LIU X L,DONG C.Case-based reasoning in struc-tural prelim inary design for high-rise buildings[A].Pro-ceedings ICAIE’98[C].[s.l.]:[s.n.],1998.
[33]邢方亮,王光远.基于SOFM实例推理系统的结构选型[J].工程力学,2003,20(1):1-6.
[34]ZHANG Sh ihai,LIU X iaoyan,OU Jinp ing,et al.CBR,KDD and sm art algorism s based design m ethodsfor h igh-rise structure form-selection[J].Pac ificSc ience Review,2002,4:30-35.
[35]张世海.高层建筑结构智能选型的理论与方法研究[D].哈尔滨:哈尔滨工业大学,2003.
[36]FAN Jianua.An overview of data m in ing and know l-edge d iscovery[J].Comput Sc i&Technol,1998,13(4):348-368.
[37]王光远,张世海.高层建筑结构方案实例库系统及其在结构智能选型中应用[J].工程力学,2003,20(4):1-7.
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