基于信息熵理论的水文站网评价优化分析

基于信息熵理论的水文站网评价优化分析

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时间:2019-01-31

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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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