人口預(yù)測(cè)的灰色增量模型及其應(yīng)用.pdf

1、學(xué)位論文人口預(yù)測(cè)的灰色增量模型及其應(yīng)用作者：賈凌云院系：數(shù)堂丕指導(dǎo)教師：[]亙氳教援申請(qǐng)學(xué)位級(jí)別：亟專(zhuān)業(yè)名稱(chēng)：提交論文日期：授予學(xué)位日期：答辯委員會(huì)主席：廑且教堂至QQ受生量且南京信息工程大學(xué)2006年5月TheIncreasedGreyModelandItsApplicationsonPopulationPredictionAbstractnlenumberofpopulationisanimportantindexteflectth

2、edevelopmentlevelforeconomyandscalethesocialadvancementWegraspthenumberofpopulationandknowitsdevelopmentalFendexactlywhichwillbeofprofoundinfectionestablishingtheplanofnationaleconomyandtacticofsocialdevelopmentChinahast

3、hefirstlargestnumberofpopulationintheworldwhichpossessesone丘m1oftheworldpopulationTheproblemoflargepopulafionisthechieffactorrestrictingChineseeconomyandsocialadvancementThisPapel“appliesthegreysystemtheorytopredictandan

4、alysethefuturepopulationinChinawhichprovidereferencedsuggestionsforestablishingpopulationandeconomicalpokeynleGreySystemTheorywasfoundedbyProfJLDengin1982whichstudiestheuncertainsystemonthe‘‘smallsample”，“poorinformation

5、”，ie，‘partinformationknownpartinformationunkrlown”wehaveThrou吐creatingandexcavatingthelimitedinformationwecouldunderstandtherealworlddescribeitsevolvementruleandgraspitsrunningbehaviorexactlyOnthebasisofgreysystemtheoryt

6、hispaperimprovesthegreymodel，ie，addaprocessoffirstorderaccllnlulativesubtractionfor也epurposeofseparatingtheincrementpart礎(chǔ)schanges缸engthenincrementinformationprominence。weakendisturbingfactorsandrevealtheoperationallawoft

7、hesystem，thushigherprecisioncanbegainedAtthesan2etime，theauthorunitethe1atestresearchproduction，puttheincrementconceDtintonewinitialvaluegreyanddispersedgreymodelwecallNGIMandDGIMforshortTheresultsshowhigherprecisiononCh

8、ina’spopulationpredictionaccordingt0也elatestdataofChinapopulationInordertovalidatetheimpressionofgreyincrementmodelonpopulationpredictiontheauthorsetexamplesofJiangsuprovinceandthecityofShanghai，whicharethemostdevelopedr

9、egioninEastChinaAndmakepredictionsandanalysisfor血eirfuturepopulationaccordingtothelatestdataTheresultsshowthatgreyincrementmodelswillmaintainhighpredictingaccuracyinmid—andlongrangepredictionsBesides，nolargequantitiesofd

10、ataaredemandedincollectionfourtoeightsamplescanbechosenformodelingwhichisusefulespeciallywhendataaredi伍culttoobtainAnditisflexibleinmodeloperationwi血slnal]calculationsConsequentlythegreyincrementmodelisausefulnewtoolforp