【摘要】：在國際油價動蕩及替代能源需求加大的形勢下，我國煤化工產(chǎn)業(yè)依靠明顯優(yōu)勢不斷發(fā)展，已經(jīng)成為我國能源產(chǎn)業(yè)的重要組成部分。隨著近階段國家政策的引導，傳統(tǒng)煤化工項目不斷轉(zhuǎn)型升級，特別是新型煤化工項目掀起建設熱潮，并逐漸成為煤化工產(chǎn)業(yè)的發(fā)展重點。煤化工產(chǎn)業(yè)是資源、技術、資金密集型產(chǎn)業(yè)，同時對環(huán)境、安全和社會配套等條件要求較高，對此類項目進行風險評價是項目成功的重要保證，對實現(xiàn)煤化工產(chǎn)業(yè)轉(zhuǎn)型升級、保障國家能源安全及國民經(jīng)濟的可持續(xù)發(fā)展均具有重大意義。 本文主要的研究如下：首先梳理風險管理相關文獻研究及項目風險管理理論，對常用風險評價技術進行分析及對比，介紹了人工神經(jīng)網(wǎng)絡理論及其在風險評價方面的突出優(yōu)勢。其次分析煤化工項目現(xiàn)狀及其風險特點，結(jié)合專家意見，，從社會環(huán)境、技術、經(jīng)濟、管理及自然五大方面對煤化工項目進行風險識別，進而建立了由22個典型風險源構(gòu)成的煤化工項目風險評價指標體系。再次，結(jié)合專家打分法，運用人工神經(jīng)網(wǎng)絡對煤化工項目風險評價進行實證分析，構(gòu)建了煤化工項目風險評價的神經(jīng)網(wǎng)絡模型。最后利用所建立的神經(jīng)網(wǎng)絡模型對案例項目進行風險評價，得出其綜合風險水平，并依據(jù)風險評價指標體系對各風險因素進行了分析評價。本文的實證研究結(jié)果表明，利用人工神經(jīng)網(wǎng)絡對煤化工項目進行風險評價是可行的，本文所建的神經(jīng)網(wǎng)絡模型可以有效地對煤化工項目進行風險評價并最終得出項目的綜合風險水平。
[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.
【學位授予單位】：中北大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP183;F426.722

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