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1、河海大學碩士學位論文BP神經(jīng)網(wǎng)絡(luò)在大型斜拉橋施工控制中的應用研究姓名：于濤申請學位級別：碩士專業(yè)：大地測量學與測量工程指導教師：黃張裕;趙仲榮20070401AbstractWitllthefastdevelopmentofthetransportationbusinessandtheunremittinglytechniqueofbridgeconstruction，bridgeconstructiontoacrossthedegree,highlydifficultdirectiondevel
2、opmentgreatly,structuresupple,beautyandsafetyofcable-stayedbridgegraduallydriveextensiveadoption．ConstructioncontrolisanimportantpartofcaMe-stayedbridgeconstructiontechnique；itisakeytomakeSUretheconstructionqualityofbridge．Soitisanimportantworktocable
3、-stayedbridge’Sconstructioncontr01．Factorsthataffectconstructioncontrolmanyandcomplex，andtheseinformationindependenteachother．Howwillvalidexploitationistheseinformation,combinemodernmathematicstheories，builduprelatedsupervisionmodelandealTyonavalidcon
4、structioncontrol，isthemaincontentsofthistextresearch．Thefulltextcombinedwimthecharacteristicsoflargecable-stayedbridgeconstruction，researchtheartificialneuralnetworkusedtoconstructioncontrol，worksmainlydidasfollows：(1)wimtheanalyticalanddiscussionofth
5、ebasicprincipletotheartificialneuralnetwork，fromtheories，thearticleexpoundsandprovedthepossibilityoftheneuralnetworkmethodusedtoconstructioncontr01．Inthisfoundationtop，thefactorsthatinfluencecable—stayedbridge’sconstructioncontrolanditsinteractionrela
6、tionareresearched．(2)AtthefoundationofanalyticaloftheblemishmatBPstudycalculateswayexistentinphysicallyapplied，giveahomologousimprovementmethod．CombineananalyticalresulttoestablishamodelthatinkeepingwimtheBPartificialneuralnetwork，topredicttheformedge
7、aringlinecontrolofthesteelboxofcabled-bridge．(3)Aimatagreaterproblemoftheconstructiondataunitandthequantityclassdifference，theadoptionamethodofdatareturnonturning，andovercametheclassbaddatawhichinfluenceoftheastringencydisadvantagetothenetworkfromthes
8、elf-study．(4)Combinetheexampletheell百neeringofthethirdNanjingYangtzeRiverBridge，drawledupthelineformcontrolpredictionprocedurewiththeMATLABprocedurelanguage，obtainedagoodresult．(5)Comparethegraytheoriespredictionandtheneuralnetworkmethodpredic
