基于人工神经网络的煤化工项目风险评价研究

发布时间：2018-10-17 14:04

【摘要】：在国际油价动荡及替代能源需求加大的形势下，我国煤化工产业依靠明显优势不断发展，已经成为我国能源产业的重要组成部分。随着近阶段国家政策的引导，传统煤化工项目不断转型升级，特别是新型煤化工项目掀起建设热潮，并逐渐成为煤化工产业的发展重点。煤化工产业是资源、技术、资金密集型产业，同时对环境、安全和社会配套等条件要求较高，对此类项目进行风险评价是项目成功的重要保证，对实现煤化工产业转型升级、保障国家能源安全及国民经济的可持续发展均具有重大意义。本文主要的研究如下：首先梳理风险管理相关文献研究及项目风险管理理论，对常用风险评价技术进行分析及对比，介绍了人工神经网络理论及其在风险评价方面的突出优势。其次分析煤化工项目现状及其风险特点，结合专家意见，，从社会环境、技术、经济、管理及自然五大方面对煤化工项目进行风险识别，进而建立了由22个典型风险源构成的煤化工项目风险评价指标体系。再次，结合专家打分法，运用人工神经网络对煤化工项目风险评价进行实证分析，构建了煤化工项目风险评价的神经网络模型。最后利用所建立的神经网络模型对案例项目进行风险评价，得出其综合风险水平，并依据风险评价指标体系对各风险因素进行了分析评价。本文的实证研究结果表明，利用人工神经网络对煤化工项目进行风险评价是可行的，本文所建的神经网络模型可以有效地对煤化工项目进行风险评价并最终得出项目的综合风险水平。
[Abstract]:Under the situation of the turbulence of international oil price and the increasing demand for alternative energy, the coal chemical industry of our country has been developing continuously depending on its obvious advantages, and has become an important part of the energy industry of our country. With the guidance of the national policy in recent stage, the traditional coal chemical engineering projects have been continuously transformed and upgraded, especially the new coal chemical engineering projects have set off a construction upsurge, and gradually become the focus of the development of coal chemical industry. The coal chemical industry is a resource, technology, capital intensive industry, at the same time the environment, safety and social supporting conditions are high, the risk evaluation of such projects is an important guarantee for the success of the project, to achieve the transformation and upgrading of the coal chemical industry. It is of great significance to ensure the national energy security and the sustainable development of the national economy. The main research of this paper is as follows: firstly, this paper combs the risk management related literature research and the project risk management theory, analyzes and compares the common risk assessment technology, introduces the artificial neural network theory and its outstanding advantage in the risk evaluation. Secondly, it analyzes the present situation of coal chemical project and its risk characteristics, combines the expert opinion, carries on the risk identification to the coal chemical project from the social environment, the technology, the economy, the management and the nature five aspects. Furthermore, the risk evaluation index system of coal chemical engineering project is established, which is composed of 22 typical risk sources. Thirdly, combining the expert scoring method, using artificial neural network to carry on the empirical analysis to the coal chemical engineering project risk evaluation, constructed the coal chemical industry project risk evaluation neural network model. Finally, the comprehensive risk level of the case project is obtained by using the established neural network model, and the risk factors are analyzed and evaluated according to the risk evaluation index system. The empirical results of this paper show that it is feasible to use artificial neural network to evaluate the risk of coal chemical projects. The neural network model established in this paper can effectively evaluate the risk of coal chemical engineering project and finally obtain the comprehensive risk level of the project.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP183;F426.722

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