基于BP神经网络的矿产资源综合区划功能分区方法研究 |
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引用本文: | 杨博,吕新彪,魏彦芳. 基于BP神经网络的矿产资源综合区划功能分区方法研究[J]. 国土与自然资源研究, 2016, 0(1): 66-70. DOI: 10.3969/j.issn.1003-7853.2016.01.017 |
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作者姓名: | 杨博 吕新彪 魏彦芳 |
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作者单位: | 1. 中国地质大学 武汉 资源学院,湖北武汉430000; 甘肃省国土资源厅,甘肃兰州730000;2. 中国地质大学 武汉 资源学院,湖北武汉,430000;3. 甘肃煤炭地质勘查院,甘肃兰州,730000 |
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基金项目: | 甘肃省工业发展“六大行动计划”专项经费 |
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摘 要: | 开展矿产资源综合区划功能分区研究,对进行差别化管理政策的制定、空间分区管理有理论和实践意义。在分析矿产资源综合区划影响因素的基础上,构建以资源条件、开发基础、生态条件、区域经济潜能为准则层的矿产资源综合区划二级区划的指标体系和分区体系。分析和讨论了矿产资源综合区划二级区划分区方法,并采用BP神经网络方法对甘肃省矿产资源综合区划二级区划进行分类研究,将甘肃省划分为重点发展、一般发展、限制发展和禁止发展4类功能区。结果表明,BP神经网络分类结果符合实际,是对传统区划方法的重要补充。
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关 键 词: | 综合区划 矿产资源 BP神经网络 功能分区 |
The Comprehensive Regionalization Function Partition Method Research Based on BP Neural Network |
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Abstract: | Research on mineral resources comprehensive regionalization functional partition has theoretical and practical significance for differential management policy, space partition management. On the basis of analyzing the factors affecting mineral resources comprehensive regionalization, build mineral resources comprehensive regionalization secondary zoning index system and partition system based on resource conditions, development, ecological conditions, regional economic potential for rule layer. Analysis and discusses the comprehensive regionalization secondary mineral resources districts partition method. Research Gansu province comprehensive regionalization secondary division classification using BP neural network method. The Gansu province has divided into four kinds of functional areas: the key development, the general development, the limited development and the prohibited development. The results show that the BP neural network classification results are reality, it is the important supplement of traditional division method. |
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Keywords: | comprehensive regionalization mineral resources BP neural network Functional partition |
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