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Environmental impact assessment model of overall land-use planning based on BP artificial neural network

机译:基于BP人工神经网络的整体土地利用规划环境影响评价模型

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摘要

In view of the problems existing in the evaluation methods of land overall planning, such as excessive evaluation error and large root mean square error, this paper proposes to design an effective environmental impact assessment model for land overall planning. The influence of social, economic and ecological environment in the overall land planning was analysed to build the environmental impact index system of the overall land planning. GRNN was used to screen the indexes with different degrees of influence, MIV was introduced to screen the index values, and rank correlation coefficient among the indexes was controlled. The indexes obtained after screening were input into BP artificial neural network to build an environmental impact assessment model of overall land planning. The experimental show that the mean absolute error is about 1.6%, and minimum root-mean-square error is about 0.01.
机译:鉴于土地总体规划评估方法存在的问题,如过度评估误差和大的根均线误差,提议为土地总体规划设计有效的环境影响评估模型。 分析了社会,经济和生态环境对整体土地规划的影响,建立了整体土地规划的环境影响指标体系。 GNN用于筛选具有不同程度的影响的索引,引入MIV以筛选索引值,并控制索引之间的秩相关系数。 筛选后获得的指标被输入到BP人工神经网络中,以构建整体土地规划的环境影响评估模型。 实验表明,平均绝对误差约为1.6%,最小根平均误差约为0.01。

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