公共工程项目风险评价的神经网络方法

A neural network model of risk analysis for public construction project

公共工程项目整个生命周期中存在着大量的不确定性因素．在详细分析公共工程项目内外环境影响因素的基础上，建立了公共工程项目风险评价指标体系，并构造了一种适用于高维输入的神经网络模型及改进算法，建立了网络自组织调整隐节点优化规则．然后采用模糊综合评价确定各风险因素的数值化评价值，结合构造的高维神经网络模型对公共工程项目投资风险的概率大小进行综合评判，并建立了一种风险预警机制．最后结合案例，对公共工程项目风险评价作出了较为客观的评价，该方法有效地弱化确定权重时的人为因素；为解决复杂的公共工程项目风险综合评价提供了一种新的方法和思路．

There are large numbers of uncertainty factors in the lifecycle of a public construction project. Based on the detailed analysis of the internal and external factors that influenced the public project, this paper has built an index system for risk assessment of public construction projects, structured a neural network and its updated algorithm which is suitable for multi-dimension inputs and established the adjusting and optimizing rules which are used to select automatically the proper number of hidden nodes for network. Furthermore, the fuzzy integrative assessment is used to confirm the numerical value of various risky factors, and this evaluation system combined with the structured neural network model can comprehensively and effectively assess the risk probability of public construction project,And then this paper presents a previous risk-alarm system. At last this model is used in a public construction project case, and the evaluation is comparatively objective. This method can effectively avoid the subjectivity of confirming the risky factors＇ weight. A new method for the investors to solve the problem about the integrative assessment of public construction project risk is provided in this paper.