Risk management evaluation based on elman neural network for power plant construction project

Abstract

Risk management is very important to the power construction. The power plant construction project risk management means the uncertain influence on construction project goals and production operation management throughout the life cycle which could cause the losses made by uncertain events. The purpose of this paper is to establish an evaluation model for risk management evaluation. Firstly, the method of principle component analysis were used to deal with the original indexes, it selects the factors which made more influence for power plant construction evaluation through the method to pre-process all the influenced factors. Secondly, the Elman neural network(ENN) model was adopted to establish an evaluation model and classify the evaluation result. It performs well with small sample set. This was a new thought for the Elman neural network to be used in risk management evaluation for power plant construction project and it could make a more objective evaluation to the contract risk in power construction project combined with cases. Comparing with AHP and FUZZY evaluation model, this new method can achieve greater accuracy. © 2010 Springer-Verlag Berlin Heidelberg.