基于支持向量機(jī)和BP神經(jīng)網(wǎng)絡(luò)的天津市水產(chǎn)品冷鏈物流需求預(yù)測研究

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Abstract： Inorder toimprove theacuracyofdemandforecasting forcoldchainlogisticsofaquatic products，thispaperusesa forecasting methodbasedonsupportvector machines.ThispaperfirstusesGreyRelationalAnalysistoselectrelevantindicators affectingdemandforecastingforcoldchainlogisticsofaquaticproducts，andtheninputssampledataintothemodelforlearning. Finally，amodelisconstructedtodescribethenonlinearreltionshipbetweenaquaticproductcoldchainlogisticsdemandand influencing factors.Thepapertakesthecoldchainlogisticsdemandof Tianjinaquaticproductsasan example，andthesiulation resultsshowthatsupportvector machineshavehigherpredictionacuracythanBPneuralnetworks inaquaticproductcold chainlogisticsforecasting，sotheuseofsupportvectormachineforecastingmodelhasabroaderaplicationprospectinaquatic product cold chain logistics demand forecasting.

Key Words： aquatic products; cold chain logistics; demand forecasting; support vector machines; BP neural networks

0引言

“冷鏈”是一種包括從生產(chǎn)、加工、儲(chǔ)存、運(yùn)輸?shù)戒N售等各階段的溫度控制在內(nèi)的一套系統(tǒng)，以確保商品的新鮮度和質(zhì)量。（剩余5333字）