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《基于統(tǒng)計模型的汛期降水預(yù)測分析——以義烏市為例》由會員上傳分享，免費在線閱讀，更多相關(guān)內(nèi)容在行業(yè)資料-天天文庫。
1、萬方數(shù)據(jù)Basedonthefloodseasonprecipitationofyiwuastheresearchobject，thispaperattemptstouseneuralnetworkpredictionmethodandthresholdautoregressivemodelrespectivelytostudythefloodseasonprecipitationofyiwu．Thispaperchosetheelninoeventsandthesubtropicalhighridgelinepositionasantecedentinfluencedfac
2、torswhichhavegoodresponseoffloodseasonprecipitationofyiwu，49yearsof1959-2007floodseasonprecipitationasthetrainingsample，and4yearsoffloodseasonprecipitationof2008—201astestsamples．Thetwomodelswereanalyzedbythreeaspects：thehistoricalsamplefittingprecision，theforecastresultsofindependentsample
3、andactualforecastability．Thefinalresultisusedtoverifythepossibilitytousetheneuralnetworkmodelandthethresholdautoregressivemodelforfloodseasonprecipitationforecastinyiwu，andalsoprovidesthebasisofthetheoryandpracticeoffloodseasonprecipitationforecastmodelinthecomingyears．Themainconclusionsoft
4、hisstudyaresummarizedasfollows：(1)Thispaperstudiesthecharacteristicsoffloodseasonprecipitationofyiwu，andalsothemainfactorsinfluencingprecipitation，provedthefloodseasonprecipitationofyiwuhasagoodresponsetosolaractivity,elninoevents，andpositionofsubtropicalhighridgeline．Onthebasisofmanyresear
5、cherstostudyconclusion，thispaperchoseelninoeventsandthesubtropicalhighridgelinepositionasimpactfactorstoestablishmodels．Thefinaldataresultsconfirmedthatitcanignificantlyreducetheprecipitationforecasterrorwhileselectingtheelninoeventsandpositionofsubtropicalhighridgelineastheearlystageofthei
6、mpactfactor．(2)Neuralnetworkforecastmodelandthethresholdautoregressivemodelareeffectiveprocessingnonlinearhydrologicsystemmodeloffloodseasonprecipitationforecastofyiwucity．BPneuralnetworkforecastingmodelisbetterwhenitcomestothehistoricalsamplefittingprecision，theforecastresultsofindependent
7、sampleandactualpredictionability．However，thedataofneuralnetworkforecastmodelandthresholdpredictionmodelareinsufficient，SOtheprecisionoftheirresultsneedslmprovmg．Keywords：NeuralNetworkForecastModel；ThresholdAutoregressiveModel；FloodSeasonPrecipitation；Imp
