基于?LM-BP?神经网络模型的高速铁路沿线环境影响评价研究

为研究高速铁路项目对生态环境的影响,以一种改进的BP神经网络算法为基础,构建了LM-BP三层前馈神经网络综合评价模型,以长益常城际铁路项目为研究实例,在划分生态环境影响评价级别,以及构建项目建设期生态影响评价指标的基础上,运用LM-BP神经网络模型对项目环境影响进行评价。结果表明,长益常城际铁路对生态环境具有较小的短期影响和极小的中期影响。该模型在收敛速度和寻找全局最优点方面具有优势。

A Research on Environmental Impact Assessment along High-Speed Railways based on LM-BP Neural Network

To analyze the impact of high-speed railway projects on the ecological environment, based on an improved BP neural network algorithm, a LM-BP three-layer feed-forward neural network comprehensive evaluation model is constructed. Taking Changde-Yiyang-Changsha intercity railway as a research example, this paper uses this LM-BP neural network model to evaluate the environmental impact on the project on the basis of dividing the ecological environment impact assessment level and constructing the ecological impact evaluation index during the construction period of the project. The results show that Changde-Yiyang-Changsha intercity railway has a little short-term impact and minimal medium-term impact on the ecological environment, which indicates that the model has advantages in convergence speed and searching for global optimal points.