差分蝙蝠算法在精准扶贫中的应用  

Application of DEBA for Targeted Poverty Alleviation

作　　者：李倩[1] 陈亮[1] 李长英[1] 朱元凯[1] LI Qian;CHEN Liang;LI Chang- ying;ZHU Yuan- kai(Department of Information Technology, Taishan Polytechinic, Tai＇an, 271000, China)

机构地区：[1]泰山职业技术学院信息技术系,山东泰安271000

出　　处：《泰山学院学报》2018年第3期67-69,共3页Journal of Taishan University

摘　　要：将差分蝙蝠算法引入到精准扶贫工作的贫困家庭识别环节,构造了基于差分蝙蝠算法的贫困家庭识别算法.该算法有效的减少了由主观因素带来的偏差问题,使真正的贫困家庭得到国家扶持,脱离贫困,走向富余.以齐河县为样本进行贫困家庭识别,与同期该区域人工确定的贫困家庭基本符合,并排除了部分不符合扶持条件的家庭,基本达到了精准扶贫的目的.By applying DEBA to the poor family identification of precision poverty alleviation,we build the algorithm based on the differential bat algorithm for poor family recognition. The algorithm effectively reduces the deviation caused by subjective factors,let the real poor families get the support of the state from poverty to surplus. This paper takes Qihe as a sample to identify poor families,it is basically in line with the needy families identified by the region in the same period,exclude a part of the family that does not meet the conditions of support,the goal of precision poverty alleviation is basically achieved.

关 键 词：精准扶贫 贫困家庭识别 差分蝙蝠算法 贫困剥夺矩阵 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]