新型城镇化发展中的山东省城市发展水平综合评价与预测

发布时间：2018-06-29 03:37

本文选题：城镇化 + 主成分分析　；参考：《山东师范大学》2017年硕士论文

【摘要】：“十二五”发展期间,山东省根据新时期科学发展观的要求,提出了城镇化发展纲要。本文在山东省新型城镇化的要求下,从山东省城市发展分类、城市发展水平以及新型城镇化的前景预测这三个角度出发,对发展中的山东省城市发展水平进行实证研究。本文选取了山东省统计年鉴中关于17个地级市的33个城市发展指标,对数据进行标准化后,运用主成分分析方法提取了 3个主成分对33个指标进行综合评估,通过构造综合得分函数计算了各地级市的综合得分并排序,又选择了系统聚类法和k-means聚类法进行聚类分析,最终得到如下结论:整体上山东半岛的东部地区城市发展水平优于西部地区,青岛市、济南市、烟台市、潍坊市这四个城市的综合发展水平优于其他地级市,而聊城市、枣庄市、菏泽市这几个西部城市在综合评价中表现较差。同时,为对山东省城镇化水平做预测,本文根据2002-2016年城镇化率数据分别选择诺瑟姆曲线模型、GM(1,1)灰色预测模型和局部线性的非参数方法进行建模和预测,根据预测结果可推断:到2020年山东省的城镇化水平基本可以达到预期目标。本文最后结合研究结果对山东省发展提出了有针对性的建议。
[Abstract]:During the development of the Twelfth Five-Year Plan, Shandong Province put forward the outline of urbanization development according to the requirements of the scientific development view in the new period. Under the requirement of new urbanization in Shandong province, this paper makes an empirical study on the developing level of Shandong city from three angles: the classification of urban development, the level of urban development and the forecast of the prospect of new urbanization. In this paper, 33 city development indexes of 17 prefecture-level cities in Shandong Province Statistical Yearbook are selected. After standardizing the data, three principal components are extracted by principal component analysis (PCA) to evaluate the 33 indexes synthetically. By constructing the comprehensive score function, the comprehensive score of each prefecture-level city is calculated and sorted, and the systematic clustering method and k-means clustering method are selected for clustering analysis. Finally, the following conclusions are drawn: on the whole, the level of urban development in the eastern part of Shandong Peninsula is better than that in the western region, and the comprehensive development level of the four cities in Qingdao, Jinan, Yantai and Weifang is superior to that of other prefecture-level cities, while Liaocheng City, Zaozhuang, Heze these western cities in the comprehensive evaluation of poor performance. At the same time, in order to predict the urbanization level of Shandong Province, this paper selects the Northam Curve Model GM (1K1) grey forecasting model and the local linear nonparametric method to model and predict the urbanization rate data from 2002 to 2016, respectively. According to the forecast results, we can infer that the urbanization level of Shandong Province can basically reach the expected goal by 2020. In the end, the paper puts forward some suggestions on the development of Shandong Province based on the research results.
【学位授予单位】：山东师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F299.27

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