基于BP神经网络的县域新城UGB预测

The Prediction of Urban Growth Boundary Based on BP Artificial Neural Networks

城市增长边界(UGB)最早是西方国家用于控制城市的蔓延,近年来被国内学者引入我过城市发展研究。其目的是防止城市的蔓延,从而保护土地资源的一种城市扩张最大边界的限制工具,确保在限定边界范围以内对于建设城区发展的土地最大化利用。本文通过对文献资料和城市统计年鉴的梳理以及数据的整理,探究BP神经网络在建立县域城市增长边界的预测模型中的应用。

Urban growth boundary UGB was first used to control urban sprawl in western countries and introduced by domestic scholars in recent years.It is a limiting tool for the maximum boundary of urban expansion to prevent urban sprawl and protect land resources,so as to ensure the maximum utilization of land for urban development within the limited boundary range.This paper explores the application of BP neural network in establishing the prediction model of county urban growth boundary by sorting out literature and city statistical yearbook as well as data.