Research On Risk Evaluation Of Coal Chemical Projects Based On Artificial Neural Network

In the situation of volatile prices of international oil and increased demand for alternativeenergy, relies on its significant advantages, China’s coal chemical industry has developed to animportant part of China’s energy industry. With guidance of the recent national policy,traditional coal chemical projects continue transiting and upgrading, particularly, new type ofcoal chemical projects set off an upsurge and have become the focus of coal chemical industry. Coal chemical industry is a resource, technology, capital-intensive industry, and the requiresof environment, safety, social supporting and other conditions are comparatively higher. Riskevaluation for such projects is an important guarantee for the success of the projects, and italso has great significance for the transformation and upgrading of coal chemical industry,ensuring national energy security and sustainable development of the national economy.The main researches are as follows: Firstly, sort out the relevant literature researches thetheories of project risk management, analyze and compare risk assessment techniques thatcommonly used, introduce the Artificial Neural Network theory and its outstandingadvantages in risk assessment. Secondly, analyze the present situation of coal chemicalprojects and their risk characteristics, combining with expert opinions, identify risks of coalchemical projects in the social environment, technology, economics, management, and naturalaspects, and then establish a risk evaluation index system for coal chemical projects which iscomposed of22typical risk sources. Thirdly, combining the expert scoring method, conductan empirical analysis for coal chemical projects risk assessment applying Artificial NeuralNetwork, build a neural network model for coal chemical project risk evaluation. Finally, usethe established neural network model to assess the risk of the case, obtain the risk level,analyze and evaluate various risk factors based on the risk evaluation system. Research results show that the Artificial Neural Network for risk evaluation of coal chemical projects isfeasible, the Artificial Neural Network model established in this paper is effective, and it canobtain the consolidated risk level of projects.