基于数据场K-means聚类的农村贫困人口精准分级研究——以贵州省某镇为例
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摘要
综合考虑贫困人口分级单指标和多指标,提出了一种基于数据场K-means融合聚类的农村贫困人口精准分级方法,该方法先由数据场势函数得到初始聚类的个数与聚类中心,再将其导入K-means聚类算法得到最终分级结果,有效地解决了传统K-means算法需要主观给定聚类参数的问题。最后,以贵州省某乡镇贫困人口数据为例进行实证分析,结果表明,该融合聚类方法更简洁、高效,能够为农村贫困人口分级提供科学合理的参考。
Considering the single index classification and the multi-index classification of the rural poor, an accurate classify method for the rural poor based on data field and k-means clustering is proposed which combines the data field with the k-means algorithm. The method firstly obtains the number of clusters and the cluster center determined by the potential function. Then, it uses the K-means clustering algorithm to obtain the final grading result, which effectively solves the problem that the traditional K-means algorithm needs subjectively given parameters. Finally, an empirical analysis is made, taking a town in Guizhou Province as an example. Result shows that the method is effective and feasible, providing a new idea for the rural poor classification.
Considering the single index classification and the multi-index classification of the rural poor, an accurate classify method for the rural poor based on data field and k-means clustering is proposed which combines the data field with the k-means algorithm. The method firstly obtains the number of clusters and the cluster center determined by the potential function. Then, it uses the K-means clustering algorithm to obtain the final grading result, which effectively solves the problem that the traditional K-means algorithm needs subjectively given parameters. Finally, an empirical analysis is made, taking a town in Guizhou Province as an example. Result shows that the method is effective and feasible, providing a new idea for the rural poor classification.
引文
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[11] S Wang,W Y Gan,D Y Li.Data Field for Hierarchical Clustering[J].International Journal of Data Warehousing and Mining,2011,7(4):43-63.
[12] 赵贵喜,刘永波,王岩,等.数据场和K-Means算法融合的雷达信号分选[J].雷达科学与技术,2016,14(5):517-520.
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[14] 淦文燕,李德毅,王建民.一种基于数据场的层次聚类方法[J].电子学报,2006,34(2):258-262.
[15] 龚艳冰,杨舒馨,戴靓靓,等.基于数据场K-Means聚类的洪涝灾害突发事件分级方法[J].统计与决策,2018,34(20):47-49.
[16] 白描.中国精准扶贫的实践与思考——中国精准扶贫进展与前瞻研讨会综述[J].中国农村经济,2018,4:140-144.
[2] 朱梦冰,李实.精准扶贫重在精准识别贫困人口——农村低保政策的瞄准效果分析[J].中国社会科学,2017,9:90-112.
[3] 任超,袁明宝.分类治理:精准扶贫政策的实践困境与重点方向——以湖北秭归县为例[J].北京社会科学,2017,1:100-108.
[4] 米红,林昕皓,樊瑾.中国多状态农村家庭收入特征聚类与影响因素分析——基于扶贫线动态变化的视角[J].南京农业大学学报(社会科学版),2018,18(4):55-62.
[5] 朱姝,冯艳芬,王芳,等.粤北山区相对贫困村的脱贫潜力评价及类型划分——以连州市为例[J].自然资源学报,2018,33(8):1304-1316.
[6] 叶初升,赵锐.村级贫困的度量:维度与方法[J].发展经济学研究,2011,1:383-402.
[7] 谢玲,李孝坤,任秋爽,等.西南地区贫困乡村地域类型划分及减贫对策研究[J].农业现代化研究,2017,38(5):818-826.
[8] 王瑜,汪三贵.农村贫困人口的聚类与减贫对策分析[J].中国农业大学学报(社会科学版),2015,32(2):98-109.
[9] 许家楠,张桂珠.基于数据场的数据势能竞争与K-Means融合的聚类算法[J].计算机应用与软件,2017,34(12):266-272.
[10] S Alkire,J Foster.Counting and Multidimensional Poverty Measurement[J].Journal of Public Economics,2011,95(7):476-487.
[11] S Wang,W Y Gan,D Y Li.Data Field for Hierarchical Clustering[J].International Journal of Data Warehousing and Mining,2011,7(4):43-63.
[12] 赵贵喜,刘永波,王岩,等.数据场和K-Means算法融合的雷达信号分选[J].雷达科学与技术,2016,14(5):517-520.
[13] S L Wang,D K Wang,C Y Li,et al.Clustering by Fast Search and Find of Density Peaks with Data Field[J].Chinese Journal of Electronics,2016,25(3):397-402.
[14] 淦文燕,李德毅,王建民.一种基于数据场的层次聚类方法[J].电子学报,2006,34(2):258-262.
[15] 龚艳冰,杨舒馨,戴靓靓,等.基于数据场K-Means聚类的洪涝灾害突发事件分级方法[J].统计与决策,2018,34(20):47-49.
[16] 白描.中国精准扶贫的实践与思考——中国精准扶贫进展与前瞻研讨会综述[J].中国农村经济,2018,4:140-144.