Research on the Prediction Model of Transformer Bidding

Abstract

Aiming at the problem of transformer manufacturing enterprises bidding is lacking scientific theoretical guidance and low bid probability, in order to predict the next bid price, based on principal component analysis (PCA) and artificial neural network (ANN) pre-tender estimate forecast model is proposed. The model uses PCA to preprocess the original high dimensional data, select principal components (PC) as the radial basis function (RBF) neural network's input. PCA eliminates the correlation of the input variables, at the same time of simplifying the structure of ANN, improving the accuracy of the prediction model. The simulation results show the applicability of the pre-tender estimate forecast model.