CAJ | 학술논문

在已有研究的基础上,运用人工神经网络的理论和方法,构建了BP神经网络模型,并对2008年陕西省83个县的县域城镇化水平进行了测度。结果表明：陕西省县域城镇化水平存在显著分异,评价结果与专家的判断基本一致。陕北、关中地区县域城镇化水平较高,陕南则相对较低,各自区内差异明显。可见,BP神经网络模型运用于县域城镇化水平简单、实用,且有效避免了人工赋权的主观性,具有良好的应用前景。
재이유연구적기출상,운용인공신경망락적이론화방법,구건료BP신경망락모형,병대2008년합서성83개현적현역성진화수평진행료측도。결과표명：합서성현역성진화수평존재현저분이,평개결과여전가적판단기본일치。협북、관중지구현역성진화수평교고,협남칙상대교저,각자구내차이명현。가견,BP신경망락모형운용우현역성진화수평간단、실용,차유효피면료인공부권적주관성,구유량호적응용전경。
Based on BP neural network model and GIS technology,this article makes a comprehensive assessment on the county-level urbanization in Shaanxi Province.The results show that the characteristics of county-level urbanization are convex distribution.In Guanzhong area counties are also characterized with a high comprehensive development level and less regional differences.In the north of Shanxi Province,counties with high level urbanization development appear to cluster.In the south of Shanxi Province,the levels of the comprehensive development of most counties are low.This article also reveals that BP neural network model applied to the county-level urbanization is simple,practical,but an effective way to avoid the subjectivity of human empowerment and has a good prospect.