极限学习机方法在电力线路建设成本估算中的应用研究
Research on Cost Estimation of Power Lines Construction Projects Based on Extreme Learning Machine Method
-
摘要: 为了提高我国电力工程建设成本概预算方法的客观性和科学性, 根据电力线路建设的影响因素, 结合单隐层前馈神经网络(SLFN)的特点, 提出了基于极限学习机(ELM)的电力线路建设成本估算的方法。在分析影响电力线路建设成本的因素和归纳电力线路建设工程的相关具体成本项目的基础上, 建立各因素和电力建设成本之间的关系集合, 构建基于极限学习机的电力线路建设成本估算神经网络模型, 并利用极限学习机算法对该网络模型进行训练, 确定网络中的相应参数。算例仿真说明:在电力线路建设成本估算领域, 相对于BP网络, ELM不仅速度极快, 而且结果良好, 泛化性能也较优。Abstract: In order to estimate the power engineering project budget in our country more objectively and scientifically, a mathematical model based on the Extreme Learning Machine (ELM) to estimate the cost of power lines construction projects is proposed in this paper by combining with single hidden layer feedforward neural networks (SLFN) method. On the basis of the analysis on the factors that affect the power line construction cost and relevant cost events of the projects, the relation sets between these factors and construction costs are built, and the ANN model for cost estimation of power lines construction projects based on extreme learning machine method is set up. In addition, the ELM is used to train the artificial neural networks to determinate its weight parameters. The simulation results show that not only the simulation speed of ELM is fast, but also the model has generalization performance relative to BP networks in the field of power line construction cost estimation.