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ID:32136952
大小:8.32 MB
页数:81页
时间:2019-01-31
《基于信息熵理论的水文站网评价优化分析》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、AbstractAsthecartierofhydrologicinformation,Hydrologicnetworklayoutdirectlyaffectstherepresentativenessandresearchvalueofhydrologicaldataprovidedbythehydrologicnetworkontheanalysisofinherentlawandcharacteristicsforbasin.However,theproblemof’’datafullybutlackofinform
2、ation”appears.Alargeamountofmanpowerandresourcesisputintotheconstructionofhydrologicnetwork,butthehydrologicdataproducesredundantinformation,whichhasbroughtinconvenienceandinterferencetotheresearchandapplication.Sowecanoptimizethehydrologicnetworktogetthemaximalinfo
3、rmation,whichcannotonlysaveresourceandinvestmentforhydrologicalconstruction,butalsoprovidescientificandsystematichydrologicaldataforhydrologyandwaterresourcesresearch.Thetraditionalnetworkoptimizationmethodhascertainlimitsanddisadvantages,andthispaperintroducedthein
4、formationEntropywhichisameasureoftheuncertaintyorinformationofsystem.Asitbasedoninformationtheory,informationentropymethodisdifferfromtraditionalmethodofnetworkoptimization.Itcanquantifytheamountofinformationprovidedbyasiteandtransmitedbetweensitesfromtheangleofsyst
5、ematicnessandintegrity,andestablishevaluationmodelandnetworkoptimizationmodeltoevaluateandoptimizethelayoutofthenetwork.Thispaperresearchsandanalysisthenetworkevaluationandoptimizationmodelbasedoninformationentropycombiningwiththeinstance,tryingtoprovidesanewfeasibl
6、enetworkoptimizationmethodforriverbasin.Themainresearchcontentsandresultsareasfollows:(1)Basedontherelatedbasicinformationentropytheory,andaccordingtothecharaeteristiesofthewatershedhydrologicnetworkanddata,whichisthetransferability,correlationandattenuationbetweens
7、itehydrologyinformation,thispaperdemonstratethereasonablenessandfeasibilityofhydrometricnetworkevaluationandoptimizationmethodbasedoninformationentropy,tolaythetheoreticalfoundationforfurtherexploration.(2)OnthebasisoftWOexistingmodelswhichisusedtodescribethelawofin
8、formationtransmissionbetweensites:transinformation—distancemodel(T-DModel)andcorrelation-distancemodel(C—DModel),Thispaperputforwardtwonew
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