BP Neural Network Based On The "Super Agricultural Docking" Type Performance Evaluation Of Supply Chain

The Ministry of Commerce, the Ministry of agriculture in2008Decemberjointly issued the" on" super agricultural docking" pilot work notice"(tobuild2008)(No.487), started in the national deployment" super agriculturaldocking" pilot job. The announcement points out, produce " super agriculturaldocking" is to reduce the circulation link, the agricultural product circulation costeffective means, is to solve the fresh produce to sell difficult basic way, on theestablishment of modern agricultural products circulation system, increase theincome of farmers and promote rural development has important realisticsignificance. Notice also pointed out," supermarket+professional cooperation+farmer" mode is the" super agricultural docking" support the main mode ofdevelopment.The" super agricultural butt"," super agricultural docking" type of supplychain related concepts, patterns were defined. Application of4D balancedscorecard, we selected10classical sample index architecture" docking" superagricultural supply chain performance to evaluate a system, they are theprofitability, asset turnover ratio, cash flow time, customer satisfaction, marketexpansion rate, response time, inventory turnover rate, defect rate, advancedtechnology, information sharing degree, and gives each performance indexmeasurement method, according to the collected a supermarket" super agriculturaldocking" process related data, an evaluation period, the performance evaluationindexes of pretreatment. Then determine the structure of BP neural network layer(the input layer, hidden layer and output layer, each layer) the number of nodes,thereby completing the structure of BP neural network model design. Networkafter the completion of the design, application design on network training, untilthe network output error is reduced to an acceptable level, building on the successof BP neural network based on the supermarket" super agricultural docking" typeof supply chain performance evaluation model. The collection of the supermarketto another set of data, the model is tested, proving its effectiveness.This thesis constructs a" super agricultural docking" type of supply chainperformance evaluation index system, uses BP neural network to evaluate it, provethat the use of BP neural network evaluation method of" super agriculturaldocking" type of supply chain performance evaluation is feasible, as the" super agricultural docking" supply chain performance evaluation provides a newperspective. Along with the" super agricultural docking" theory and practice ofcontinuous improvement, evaluation methods will also emerge in an endlessstream. Based on BP neural network" super agricultural docking" type of supplychain performance evaluation method is an important part of.