| Warehousing activities is anindispensable important segment in the circulation of commodities as well asthe process of social reproduction; it plays an important role in the GDP,which is necessary and important for any enterprise. From the angle oflogistics, warehousing is an important component of logistics, with a fuzzy understanding about intelligent storage in domestic,it isstill relatively lag on intelligent warehousing evaluation. Therefore theestablishment of a fair intelligent quality evaluation system appearsparticularly important.Under this background, this paper conducts in-depthexploration and study on evaluation to the intelligent quality of intelligentwarehousing, which combines qualitative and quantitative research indexes. Firstly,it introduced the research background and significance, and reviewed on somedomestic and aboard researches. Secondly, it defines some relevant conceptssuch as intelligent warehousing, intelligent quality, BP neural network, which generalizedfrom the relevant literatures. It constructs5grade-first indexes and26level-two indexes.This paper conducts an intelligent quality evaluationmodel of intelligent warehousing based on BP neural network. In the demonstration,it chooses S company Beijing NO.1to undertake evaluating through thetraditional grey hierarchy evaluation method and fuzzy comprehensive evaluationmethod, two methods have the consistency of the results. It proves that thetraditional evaluation method is practical and scientific, and then the BPneural network was tested by samples, and it was turned out to be better fittedfor S company. Because the BP neural network has a more generalized ability, soit can evaluate the S company's warehouse intelligent quality evaluation in thenation, through the evaluation of S company will have a comprehensiveunderstanding of the status quo, and then improve warehouse intelligent qualitybased on the current situation and continuously in order to improve the market competitiveness of the goal. |
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