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| Research on rurality differentiation of county areas in Shaanxi Province based on BP neural network |
| ZHAO Taotao, BAI Jianjun, SHANG Zhonghui |
| College of Tourism and Environment, Shaanxi Normal University, Xi'an 710062, China |
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Abstract The study applys the BP neural network to determine the index weight of rurality, which provides a new way to measure the rurality and lays the theoretical foundation of county economy development of Shaanxi Province. To establish a comprehensive index system of the rurality evaluation, we take 83 counties as research units based on the thoughts of the integration of urban and rural areas. We firstly use BP neural network to determine the index weight, and calculate the rurality index on the platform of Visual Studio 2010. Then, ArcGIS and GeoDA are utilized to classify the categories. Therefore we analyze the numerical and spatial differentiations of rurality quantificationally. It is viable to use the BP neural network to evaluate the weight and intensity. There is serious polarization of rurality in Shaanxi counties; The distribution is balanced in all categories. The rurality is high in the south and north of Shaanxi Province, and low in the middle part, which presents higher space relevance. Finally, we discuss the reason for the rurality disparity, and propose the method to solve the problems. The endowment of resource, economic foundation, location advantages and policies are the main factors that lead to the differences of rurality. So the counties in Shaanxi Province should take measures to adjust local conditions, and should adopt the developing models which based on their own characters and the connections between counties. Therefore, we intensify the urban-rural integration to realize county coordinated development in Shaanxi Province.
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Received: 26 June 2015
Published: 12 March 2016
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基于BP神经网络的陕西省县域乡村性分异研究
以陕西省83个县域为实证研究单元,基于城乡一体化思想构建了乡村性综合评价指标体系,运用BP神经网络确定其指标权重,在Visual Studio 2010平台上计算乡村性指数,并借助ArcGIS和GeoDA软件划分乡村发展类型,对乡村性数值分异及空间分异进行了定量化测度和分析.运用BP神经网络确定乡村性权重及强度具有一定的可行性;陕西省县域乡村性在数值分异特征上,两极分化严重,中低、中等、中高水平县域组内均衡;在空间分异特征上,呈陕南、陕北高,关中低,东低西高的分布格局,乡村性空间关联性较强,彼此联系紧密.进而对陕西省县域乡村性差异的成因做了初步探讨,提出了县域发展的方向.
关键词：
乡村性,
县域尺度,
BP神经网络,
探索性空间分析,
陕西省
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