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ID:32062597
大小:1.66 MB
页数:55页
时间:2019-01-31
《焦化行业价格预测模型与应用分析》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、华中科技大学硕士学位论文—;——;————===——≈——=—=;——————%一ABSTRACTWiththeenteringtotheWTO,thecompetitionbetweentheenterprisesbecomesmoreandmoreintensive,andmuchofthecompetitionisontheprice.Soit'sveryimportanttoforecastandadjustthepriceaccuratelyandtimelyaccordingtothechangingofthemarketconditions.However'atpre
2、sentmostenterprisesforecastthepriceoftheirproductsnotbysciencemethodbutonlyqualitativeanalysis,anditdosenotwelladapttothecompetition.Theaimofthispaperistobuildaneffectivepriceforecastingmodelforcokingindustry.Atthebeginning,thispaperexplainsthefoundationalforecasttheories,discussesthefundament
3、alcategoryandprinciplesforforecastingandthebasicimplementsteps,andputsthefocusonthecomparisonofthesetwomethods---qualitativeanalysisandquantitativeanalysis.Then,thecokingindustryfeaturesandfactors,whichwillinfluencetheprice,areanalyzed.Withtheseanalyticalresults,themajorinfluencefactorsonprice
4、aredetermined.Throughthefurtherexplorationontherelationsbetweenthecokingproductpriceandthoseinfluencefactors,thispaperbuildssomeforecastingsub.modelsbasedondifferentinfluencefactorsrespectivelyandproposesacombinationforecastingmodelfromthem.ThemodelCantosomeextendavoidsomenegativeinfluencesofp
5、redictionprecisionfromtheinformationselectionbypeople’Ssubjectivity.AttheSametime,thismodelisalsomademoreeffectivebyadoptingaweightcoefficientcorrectmodeltoamendtheweightcoefficientofthecombinationforecastingmodeldynamically.InordertOpromotethemodel’Sadaptabilityandfullyconsidersomeinfluenceso
6、nthemodelprecisionfrommanyunpredictablefactorssuchasmarketsituationchangesandtechnologicalprogress,thehuman-machineharmonymechanismisintroducedtothismodel.Furthermore,thispaperdefmesvalidityforthemodelandprovideseffectiveverificationformulationsasthetheorybasisforevaluatingit.Attheendofthispap
7、er,thevalidityofthemodelisverifiedbythedatumfromCokingCorporationLTD.ofWuHanIronandSteelGroupCo.theresultsshowsthattheCombinationmode“Smoreaccurateandeffectivecomparedwitheachsub.model.Keywords:CombinationForecastingTimeSequenceRegressi
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