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  本文選題：建筑工程項(xiàng)目　切入點(diǎn)：指標(biāo)體系　出處：《新疆大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來,風(fēng)險評估作為風(fēng)險管理的重要組成部分,在建筑業(yè)生產(chǎn)實(shí)踐中受到越來越多的重視,建筑工程風(fēng)險評估問題成為研究的熱點(diǎn)。隨著國家援疆力度的加強(qiáng),新疆建筑行業(yè)存在較好的發(fā)展環(huán)境和機(jī)遇,因此,本地區(qū)建筑工程項(xiàng)目風(fēng)險評估研究在工程項(xiàng)目管理中顯得尤為重要。建筑工程項(xiàng)目風(fēng)險受多因素影響,本文考慮到新疆地區(qū)地域的特殊性和各風(fēng)險因素的不確定性、復(fù)雜性等基本特征,以該地區(qū)工程項(xiàng)目為例進(jìn)行風(fēng)險因素識別。在運(yùn)用層次分析法(AHP法)確定各風(fēng)險因素權(quán)重的基礎(chǔ)上,建立多層次灰色綜合評價模型,對各風(fēng)險評估指標(biāo)進(jìn)行綜合評價和排序,構(gòu)建了具有地域性特色的風(fēng)險評估指標(biāo)體系。本文在應(yīng)用多層次灰色評價方法的基礎(chǔ)上,采用基于遺傳算法優(yōu)化的神經(jīng)網(wǎng)絡(luò)方法(GA-BP神經(jīng)網(wǎng)絡(luò)),構(gòu)建了新疆地區(qū)建筑工程項(xiàng)目風(fēng)險評估模型,并應(yīng)用此模型進(jìn)行了新疆地區(qū)建筑工程項(xiàng)目風(fēng)險評估分析。GA-BP神經(jīng)網(wǎng)絡(luò)模型預(yù)測值與多層次灰色評價結(jié)果吻合良好,驗(yàn)證了GA-BP神經(jīng)網(wǎng)絡(luò)風(fēng)險評估模型的可行性。GA-BP神經(jīng)網(wǎng)絡(luò)有著較高的收斂速度和預(yù)測精度,為新疆地區(qū)建筑工程項(xiàng)目風(fēng)險評估研究提供了一種新的思路與方法。
[Abstract]:In recent years, as an important part of risk management, risk assessment has been paid more and more attention in the construction industry. The construction industry in Xinjiang has a good development environment and opportunities. Therefore, the risk assessment of construction projects in this area is particularly important in the project management. The risk of construction projects is affected by many factors. This paper takes into account the regional particularity of Xinjiang and the uncertainty and complexity of various risk factors. Taking the engineering project in this area as an example, the risk factors are identified. On the basis of determining the weight of each risk factor by using AHP), a multi-level grey comprehensive evaluation model is established, and the comprehensive evaluation and ranking of each risk assessment index are carried out. A risk assessment index system with regional characteristics is constructed. Using the neural network method based on genetic algorithm optimization, the risk assessment model of construction project in Xinjiang area is constructed, which is based on GA-BP neural network. The prediction value of GA-BP neural network model is in good agreement with the result of multi-level grey evaluation. The feasibility of the risk assessment model of GA-BP neural network. GA-BP neural network has higher convergence speed and prediction accuracy. It provides a new way of thinking and method for risk assessment of construction projects in Xinjiang.
【學(xué)位授予單位】：新疆大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TU71

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本文編號：1569901