本文關鍵詞： 工程項目質量 風險評價 粗糙集 神經網絡 指標體系　出處：《江西理工大學》2013年碩士論文　論文類型：學位論文

【摘要】：近年來，建筑業(yè)在我國得到了快速發(fā)展，建筑市場的規(guī)模也在逐漸地擴大，但由于工程項目自身具有規(guī)模大、周期長、投資高等特性，使得工程項目的質量問題越來越受到大家的重視。一旦工程項目的質量出現問題，不僅會影響到整個工程項目的交付和使用，造成經濟利益的損失，如果嚴重的話還會影響到國計民生甚至整個建筑業(yè)的發(fā)展。目前，工程項目的質量問題已經成為人們關注的焦點，人們希望通過技術控制和科學管理使得工程項目質量達到預期目標，而工程項目質量風險評價是工程項目質量風險管理中最有效的管理方法，是發(fā)現質量問題、找出問題原因和保證工程項目質量的重要依據。因此，本文對工程項目質量風險評價展開了理論和實證研究，希望能夠給我國的工程項目質量風險管理提供一定的理論依據。 本文首先從工程項目質量風險管理入手，進而對工程項目質量風險管理的相關概念和特點展開了詳細的論述。然后分析了工程項目質量風險管理的全過程，逐一對傳統的風險識別和風險評價方法進行了相關介紹，并結合工程項目自身的特點，提出了基于粗糙集_神經網絡的工程項目質量風險評價方法，同時論證了該評價方法的可行性。接下來根據工程項目施工階段的實際情況，運用相關理論和方法識別出工程項目施工階段的質量風險因素，構建出工程項目質量風險評價指標體系。最后對粗糙集_神經網絡風險評價模型進行了實證性分析。首先利用粗糙集理論對收集到的工地樣本數據進行處理，然后將約簡后的評價指標作為輸入端建立了工程項目質量風險的神經網絡評價模型，，并利用MATLAB7.0軟件工具對BP神經網絡進行訓練和檢驗。通過實證分析的結果可以看出該模型的可操作性較好，評價的效果不錯，具有一定的應用價值。
[Abstract]:In recent years, the construction industry has been developing rapidly in our country, and the scale of the construction market is also gradually expanding. However, because of the large scale, long period, high investment and so on, the engineering project itself has the characteristics of large scale, long period, high investment and so on. The quality problem of the engineering project is paid more and more attention to. Once the quality of the project has a problem, it will not only affect the delivery and use of the whole project, but also cause the loss of economic benefits. If it is serious, it will also affect the development of the national economy and the people's livelihood and even the entire construction industry. At present, the quality of engineering projects has become the focus of attention. It is hoped that the project quality can reach the expected goal through technical control and scientific management, and the engineering project quality risk assessment is the most effective management method in the engineering project quality risk management, which is to find the quality problem. To find out the cause of the problem and the important basis to guarantee the quality of engineering project, this paper has carried out theoretical and empirical research on quality risk assessment of engineering project, hoping to provide some theoretical basis for quality risk management of engineering project in our country. This paper begins with the quality risk management of engineering projects, and then discusses in detail the related concepts and characteristics of quality risk management of engineering projects, and then analyzes the whole process of quality risk management of engineering projects. This paper introduces the traditional risk identification and risk assessment methods one by one, and puts forward the quality risk evaluation method based on rough set _ neural network, combining with the characteristics of engineering project itself. At the same time, the feasibility of the evaluation method is demonstrated. Then, according to the actual situation of the construction phase of the project, the quality risk factors of the construction phase of the project are identified by using the relevant theories and methods. The quality risk evaluation index system of engineering project is constructed. Finally, the rough set _ neural network risk evaluation model is analyzed empirically. Firstly, the collected site sample data are processed by rough set theory. Then the reduced evaluation index is used as the input to establish the neural network evaluation model of engineering project quality risk. The MATLAB7.0 software is used to train and test BP neural network. The results of empirical analysis show that the model has good operability, good evaluation effect and certain application value.
【學位授予單位】：江西理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TU712.3

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本文編號：1499785