CPSO-LSSVM Model-based Risk Assessment for New Energy Project in Power Industry

摘要

With the rapid development of new energy market, accurate assessment of project investment risk has become more and more important. A novel investment risk assessment model based on prediction was proposed. Firstly, the analysis of the risk factors for new energy projects was conducted and a risk indicator system was built. Secondly, a Chaos Particle Swarm Optimization (CPSO) algorithm for parameters optimization was proposed to build the risk prediction model, on the basis of the adaptability of the Least Squares Support Vector Machine (LSSVM) to small samples. Finally, historical data related to model training and project prediction were collected to assess the risk of current project. The calculation based on an actual project showed that the model proposed in this paper had high accuracy and consequently should be widely applied.