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Research and Implementation of Intelligent Risk Recognition Model Based on Engineering Construction of Neural Network

机译:基于神经网络工程建设的智能风险识别模型的研究与实现

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Since the reform and opening up, both domestic economy and people's living level acquire great improvement. People also pay more strong attention to risk issues of on-going engineering projects' construction. At present, science and technology have stepped onto high-speed development stage and the world is rapidly changing. Uncertainty of social external condition may lead enterprises to encounter more and larger risks during the construction process of engineering projects. Traditional engineering construction risk recognition model can't already fully and effectively identify risks. Therefore a new type of intelligent risk recognition mode is in urgently needed in construction of engineering projects. This paper proposes a kind of risk recognition model based on neural network so as to intelligently recognize different forms of potential risks, thus decreasing the damage from risks to a minimum. Relevant model below is established according to characteristics of engineering projects on purpose of doing quantitative analysis of risk rating in the engineering construction industry at present. It utilizes Genetic Algorithm to correct network, whose process increases accuracy and stability of all networks. Based on neural network, this paper establishes the model which could do risk rating during the project operation process in the engineering construction industry. It also does classification and research according to characteristics of potential risks in engineering projects, thus helping a project leader to more accurately predict, prevent and control risks, which guarantees safe and smooth operation of engineering projects.
机译:自改革开放以来,国内经济和人民生活水平都收购了巨大的改善。人们还要更加强烈地关注持续工程项目建设的风险问题。目前,科技已经进入高速发展阶段,世界正在迅速变化。社会外部条件的不确定性可能导致企业在工程项目建设过程中遇到更多和更大的风险。传统的工程建设风险识别模型无法完全有效地识别风险。因此,在工程项目建设中,迫切需要一种新型的智能风险识别模式。本文提出了一种基于神经网络的风险识别模型,以智能地识别不同形式的潜在风险,从而将风险的损坏降低至最低限度。下面的相关型号是根据工程项目的特点建立的,目的是在目前进行工程建筑业风险评级的定量分析。它利用遗传算法来正确的网络,其过程增加了所有网络的准确性和稳定性。基于神经网络,本文建立了工程建设行业项目运行过程中可能会有风险评级的模型。它还根据工程项目潜在风险的特征进行分类和研究,从而帮助项目负责人更准确地预测,预防和控制风险,保证工程项目的安全和平稳运行。

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