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基于超效率DEA和人工神经网络耦合模型的畜禽养殖资源环境承载力研究——以天津市为例 被引量:1

Environmental Bearing Capacity of Livestock and Poultry Breeding Resource Based on the Couple Model of Super Efficiency DEA and Artificial Neural Network— A Case of Tianjin City
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摘要 [目的]基于超效率DEA和人工神经网络耦合模型分析天津市畜禽养殖资源环境承载力。[方法]在构建畜禽养殖资源环境承栽力评价指标体系的基础上,建立基于超效率DEA和人工神经网络耦合模型的评价模型,并以天津市为实例,对2003~2012年畜禽养殖资源环境承我力进行研究。[结果]2003~2012年天津市畜禽养殖资源环境承载力虽然不处于警戒水平,但畜禽养殖资源环境承载力整体呈下降趋势,而且2012年天津市畜禽养殖资源环境承载力已经趋近警戒水平。[结论]基于超效率DEA和人工神经网络耦合模型的畜禽养殖资源环境承栽力评价模型具有一定的科学性,耦合模型排除了人为因素干扰,充分考虑了系统内部运行规律,具有一定的应用价值和理论优蛰. [ Objective ] To research the environmental beating capacity of livestock and poultry breeding resource in Tianjin City based on the couple model of super efficiency DEA and artificial neural network. [ Method] On the basis of building the evaluation index system of livestock and poultry breeding resource environmental bearing capacity, we built up the environmental bearing capacity assessment model of livestock and poultry breeding resource by couple model of super efficiency DEA and artificial neural network, then applied the couple model to the example of Tianjin to research its environmental beating capacity from 2003 to 2012. [ Result] Environmental beating capacity of livestock and poultry breeding resource in Tianjin City was not at alert level from 2003 to 2012, but the environmental bearing capacity presented a downward trend in general. However, environmental bearing capacity of livestock and poultry breeding resource in Tianjin City was close to the alert level in 2012. [ Conclusion] The environmental bearing capacity evaluation model based on super efficiency DEA and artificial neural network is scientific. Coupling model eliminates human factors, fully considers the internal system operation rule, and has certain application value and advantage of theory.
出处 《安徽农业科学》 CAS 2016年第8期14-17,83,共5页 Journal of Anhui Agricultural Sciences
基金 中央级公益性科研院所业务费专项(2011-aepi-14)
关键词 畜禽养殖资源环境承载力 评价指标体系 超效率DEA 人工神经网络 耦合模型 Environmental bearing capacity of livestock and poultry breeding resource Evaluation index system Super efficiency DEA Artificial neural network Couple model
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