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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >Health evaluation of a regional logistics industrial ecosystem in China based on fuzzy matter-element analysis method
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Health evaluation of a regional logistics industrial ecosystem in China based on fuzzy matter-element analysis method

机译:基于模糊物元分析方法的中国区域物流产业生态系统健康评价

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摘要

The construction of a regional logistics industrial ecosystem elicits increasing attention because of the growing awareness of environment protection, and its health evaluation by considering environmental impacts is one of the kernel problems that must be addressed to promote the development of regional logistics. In this study, a comprehensive methodology based on fuzzy mathematics and matter-element analysis theory was presented to accurately evaluate the health status of the regional logistics industrial ecosystem in China. First, the forming mechanism and influencing factors of regional logistics industrial ecosystem were analyzed. Second, a fuzzy matter-element model was constructed to evaluate the regional logistics industrial ecosystem, and the weights of characteristic values of evaluation indexes for fuzzy matter-element were obtained using entropy decision method. Finally, this proposed method was applied to evaluate the logistics industrial ecosystem health of eight provinces in China. In this case, these evaluation indexes include energy consumption, logistics cost, and CO2 emissions. The results show that this method is feasible and effective, and demonstrate the promising application of the proposed model in evaluating the health status of a regional logistics industrial ecosystem and in supplying reliable data for the environmental protection of regional logistics activities.
机译:随着人们对环境保护意识的增强,区域物流产业生态系统的建设引起了越来越多的关注,考虑环境影响对其健康进行评价是促进区域物流发展的核心问题之一。在这项研究中,提出了一种基于模糊数学和物元分析理论的综合方法,以准确评估中国区域物流产业生态系统的健康状况。首先,分析了区域物流产业生态系统的形成机理及其影响因素。其次,建立了模糊物元模型对区域物流产业生态系统进行评价,并运用熵权决策法获得了模糊物元评价指标的特征值权重。最后,将该方法应用于中国八个省市的物流产业生态系统健康评价。在这种情况下,这些评估指标包括能耗,物流成本和CO2排放量。结果表明,该方法是可行和有效的,并证明了该模型在评估区域物流产业生态系统健康状况以及为区域物流活动的环境保护提供可靠数据方面的应用前景。

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