The Research And Application Of Clothing Sales Forecasting Model Based On Ahp And Bp Neural Network

For the clothing industry, enterprises, improve the operating efficiency is mainly based on two factors, one is the clothing sales forecasting accuracy, the other is a supply chain reaction speed, efficiency is the supply chain. If the prediction accuracy is high, even if the supply chain reaction speed is not fast enough, but also to achieve the high turnover of inventory and capital, visible clothing sales forecasting accuracy for the top company decision making plays an important role.In this paper, the analytic hierarchy process (Analytical Hierarchy Process, referred to as AHP) and BP (Back Propagation) combined with artificial neural network, proposes a prediction model of A-BP sales, the close combination of qualitative and quantitative prediction algorithm. The construction process of this model is:first proposed the multiple influence the sales factor, then these impact factors through AHP to establish three level hierarchical structure, the relative importance of factors levels compared to determine the weight of each factor by two two, the output of sales, the last weight value ranked in the influence of the first several factor into calculated BP neural network, obtains the forecast sales.Finally, this paper implements a forecasting system of A-BP model based on the sales, through the experiment model is better than BP neural network model prediction accuracy higher sales forecast A-BP verification conclusion.