基于Kohonen网络和DEA交叉评价耕地利用效率聚类分析

浙江农业学报

基于Kohonen网络和DEA交叉评价耕地利用效率聚类分析

（1河南理工大学测绘学院，河南焦作 454000；2河南工程学院土木工程学院，河南郑州 451191）

出版日期:2015-09-25 发布日期:2015-09-23

Cluster analysis of cultivated land use efficiency based on Kohonen network and DEA cross evaluation#br#

（1 School of Surveying & Land Information Engineering， Henan Polytechnic University， Jiaozuo 454000， China; 2 Institute of Civil Engineering， Henan Institute of Engineering， Zhengzhou 451191， China）

Online:2015-09-25 Published:2015-09-23

摘要/Abstract

摘要： 利用统计年鉴中社会经济数据，选取DEA交叉模型对耕地利用效率进行评价，并引入Kohonen神经网络对评价结果进行聚类，分析了河南省耕地利用效率的空间分布特征。结果表明，DEA交叉效率评价模型可以避免出现伪有效决策单元，且效率评价值相对较低，说明评价结果客观、准确，避免了人为确定分类指标权重的主观性。投入水平对提高耕地利用效率有促进作用，而利用程度对耕地利用效率影响较小。河南省耕地利用效率较高且较为稳定的城市有南阳、商丘、濮阳、三门峡、许昌、新乡6个城市。聚类分析结果显示，河南省耕地利用效率的空间分布呈现明显区域差异，西北部黄河中下游平原地区耕地利用效率较高，而东部和南部地区则相对较低。

关键词: 耕地利用效率, DEA评价, 交叉效率评价, Kohonen神经网络, 河南省

Abstract: In the present study， DEA intersection model was selected to evaluate cultivated land use efficiency based on social and economic data collected from the statistical yearbook， and the evaluation results were clustered with Kohonen neural network to analyze spatial distribution features of cultivated land use efficiency in Henan Province. It was shown that the DEA cross efficiency evaluation model could avoid spurious effective decision making units， and the evaluation value was relatively low， which indicated that the evaluation result was objective， accurate， and able to avoid the subjectivity of man\|made classification index weight. The increasing input level could promote the utilization efficiency of farmland， while the influence of utilization degree on cultivated land use efficiency was minor. The cultivated land use efficiency in Nanyang， Shangqiu， Puyang， Sanmenxia， Xuchang， Xinxiang， was relatively high and stable. Cluster analysis exhibited obvious regional differences in spatial distribution of cultivated land use efficiency in Henan Province. The cultivated land use efficiency in the northwest plain area was high， while the cultivated land use efficiency in the eastern and southern regions was relatively low.

Key words:

cultivated land use efficiency, DEA evaluation, DEA cross evaluation model, Kohonen neural network, Henan Province

刘轩1，牛海鹏1，董国权1，刘文锴2. 基于Kohonen网络和DEA交叉评价耕地利用效率聚类分析[J]. 浙江农业学报.

LIU Xuan1， NIU Hai\|peng1， DONG Guo\|quan1， LIU Wen\|kai2. Cluster analysis of cultivated land use efficiency based on Kohonen network and DEA cross evaluation#br#[J]. .