基于数据挖掘技术的混凝土配合比优化设计

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1、同济大学材料科学与工程学院博士学位论文基于数据挖掘技术的混凝土配合比优化设计姓名：肖瑞敏申请学位级别：博士专业：材料学指导教师：张雄20040301摘要一最佳集灰比原则●经济性原则在此基础上发展了一种基于数据库支持，并应用模糊理论的混凝土配合比设计方法。整个设计过程实际围绕着自学习、自诊断、自优化的主旨进行。将此方法用于实际工程中，获得了非常好的效果。关键词：混凝土配合比优化设计数据挖掘灰色关联人工神经网络模糊理论低收缩抗裂混凝土nAbstractTherehasbeenmorethanonehundredyearssinceconcretewasin

2、vented．SOalotofconcretemixdesignmethodshasbeendeveloped．Thesemethodsalhastheirowncharacteristicsandeachhashisstrongpoint，howeveEthesedesignmethodsareisolated．thatis。theylackthecapabilityofself-learning，self-diagnosing。self-optimizing．Ontheotherhand。inthelongdevelopingcourse，larg

3、enumbersofconcretemixproportiondatawerecollectedandrichmixingexperiencewasaccumulated，thesewereveryvaluableknowledgetreasure，buttraditionalmixdesignmethodscouldnotmakeefficientuseofthemtoguidethenewdesignandresultedinawasteofresource．So，anidealmethodshouldacquireknowledgefrOmthe

4、historyconcretemixproportiondata。thenutilizethemtoguidethecurrentdesigntooptimizethemixproportion．Itwasimpossiblebefore，butnowitcouldbeturnedintorealitywiththedevelopmentofDatabase。ArtificialNeuralNetworkandothercomputertechnology．Soanewmethodwiththecharacteristicsofself-learnin

5、g。self-diagnosingandself-optimizingispresentedandrealizedthroughthehottechnology“datamining”inthispaper．Previousconcretemixdesignmethodsarealwayspayingaffentiontothemechanicpropertyandworkablility,butdonotgiveanequaltreatmenttodurability．Sothenewmixdesignmethodpresentedinthispap

6、erspeciallytaketheshrinkageintoaccountsfromallkindsofdurabilityaccordingtothefactsthatthereexistedalotofcracksresultedfrOmshrinkagehappened。andtrytoreduceshrinkageandenhancetheresistanceofcrackofconcretebyoptimizingtheconcretemixproportion．Atthesametime．theeconomicalefficiencyis

7、alsoregardedinthedesign．TorealizethewaythatmakesuseofknowledgeacquiredfrOmhistorydatatoguidetheoptimizationofconcretemixdesign，aconcretemixproportiondatabasewithclearrelationandhighexpansibilitywasestablished。anddatacollectedfromdifferentresourCeswerefilledin。Basedonthedatabase。

8、aIllAbsttactconcretemixproportiondataminingsyst