开发区土地集约利用评价BP神经网络模型研究与应用

Research and application on intensive land use evaluation of development zone based on BP neural network model

开发区的土地集约利用程度直接关系到开发区的产业升级和可持续发展,因而如何科学地评价其土地集约利用状况具有重要意义。本文以安徽省某省级开发区为例,根据开发区土地集约利用评价规程的要求建立由14个指标组成的土地集约利用评价指标体系,并采用BP神经网络结构构建土地集约利用评价定量模型,据此测算出该开发区的土地集约利用水平并对评价结果进行了分析。研究结果表明,BP神经网络模型自学习和容错能力强,较好地克服了传统统计分析方法中主观因素的影响,使评价结果更加客观准确。

The intensive land use degree of the development zone is directly related to its industry upgrading and sustainable development,so it is of great significance to how to evaluate the condition of intensive land use of the development zone scientifically.With a provincial development zone in AnHui province as an example,this paper is based on the regulation of intensive land use evaluation of the development zone to establish indices system which includes 14 indicators for land intensive use evaluation,and uses the BP neural network to build the quantitative model of the intensive land use evaluation.Then the level of intensive land use is measured as well as the results of evaluation are analyzed.The results indicate BP neural network model has strong self-learning and fault-tolerant ability so that it can remove the impact of subjective factor in the traditional statistical method,so the results are more objective and accurate.