为了提高效率,提出了一种基于BP神经网络的工程造价预估模型.该模型在详细分析市政排水管道工程的项目特征和工作内容的基础上,找出了影响市政工程造价的主要因素,建立了造价影响因素和工程造价之间的映射关系,以工程的特征因素作为神经网络的输入向量,将所需的工程造价作为神经网络的输出向量,通过将已有相似工程的造价信息进行输入,训练网络函数,使函数不断修正改进,从而实现工程特征输入空间到工程造价输出空间的映射,达到了准确预估市政工程造价的目的.实验结果表明,本文建立的仿真模型切实可行,是比较理想的市政工程造价预估方法,可以预估到比较准确的市政工程造价.%In order to improve the efficiency, a BP neural network-based construction cost estimate model was put forward. With detailed analysis of municipal drainage pipeline engineering project characteristics and work content, the model found out the influence of the main factors of municipal engineering cost, established the mapping relationship between the cost-offecting factors and the project cost. The characteristic factors of engineering were used as the neural network's input vector, the construction cost as neural network s output vector, with the cost information of existing similar engineering as input, the network function was trained, the function was corrected and improved, so as to realize the space mapping from the engineering characteristics input space to projected and output space, and to reach the accurate estimation of municipal engineering cost. The experimental results show that the simulation model was feasible, and was an ideal municipal engineering cost estimate method, which can estimate municipal engineering drainage pipeline project cost with relatively high accuracy.
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