基于支持向量机和BP神经网络的天津市水产品冷链物流需求预测研究

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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

“冷链”是一种包括从生产、加工、储存、运输到销售等各阶段的温度控制在内的一套系统，以确保商品的新鲜度和质量。（剩余5333字）