摘要
GIS是管理和分析土地利用数据的有力工具。GIS和人工神经网络的整合提供了一种机制,可以通过减少解释数据的时间来降低对土地利用类型变化的分析成本。人工神经网络(ANNS)已被证明在解释自然资源信息方面是有效的。BP神经网络是最常用、最广泛使用的结构之一。本模型利用机器学习算法对土地利用结构优化方法做了深入研究,发现了传统方法的不当之处,在一定程度上减少政策中主观因素上的误差。该模型可以很好地预测未来土地利用的发展趋势,对土地资源合理进行安置和有效利用具有重要意义。
GIS isa powerful tool for managing and analyzing land use data. The integration of GIS and artificial neural network providesa mechanism to reduce the analysis cost of land use type change by reducing the time of interpreting data. Artificial neural network （ANNS） has been proved to be effective in explaining natural resource information. BP neural network is one of the most commonly used and widely used structures. This model using the method of machine learning algorithm for the land use structure optimization done in-depth research, found that the traditional method is wrong, to a certain extent, reduce subjective factors in policy on the error. The model can predict the development trend of land use in the future, and it is of great significance for the rational resettlement and effective utilization of landresources.
作者
卜祥斌
薛楠
刘鹏
BU Xiang-bin;XUE Nan;LIU Peng(School of Electrical and Electronic Engineering,Harbin University of Science and Technology,Harbin 150040,China)
出处
《电脑与信息技术》
2018年第5期20-23,共4页
Computer and Information Technology
基金
哈尔滨理工大学校级大创项目(项目编号:201710214159)
