Product Family Configuration Price Prediction Based On Neural Network

Abstract

In order to quickly and effectively respond to customer enquiry in the dynamic changeable market, a new method for product family configuration price prediction is proposed based on neural network with adjustable number of hidden layer nodes. Based on product family configuration history of various product variants and the corresponding prices, the relationship model between the product configuration and price is established using neural network, which is utilized to predict the market price of the newly configured product variant for some random order.