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基于ANP-BPNN的“城市矿产”开发利用多主体协同影响因素识别 被引量:1

ANP-BPNN Model Based Identification of the Factors that Affect the Multi-agent Collaboration of “Urban Minerals”
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摘要 “城市矿产”的开发利用是一个涉及多主体、多阶段的复杂过程。本文从“城市矿产”开发利用过程中涉及的五大主体出发,提取出35个行为影响因素,构建了“城市矿产”开发利用的多主体协同评价指标体系;为了避免传统模型因指标过多陷入维度灾难而导致估计有偏,本文建立ANP-BPNN模型,利用ANP计算指标权重并作为BPNN模型的输入,通过结合BPNN模型的原理,采用可微函数,实现输入和输出间的任意非线性映射,且基于模型输出与实际值之间的误差进行反向传播从而优化模型参数,使模型效果达到最佳。研究发现:社会环境、环保责任感、运输成本、回收成本以及市场环境是影响“城市矿产”开发利用多主体协同的关键指标,且不同性质、不同规模企业的指标权重存在异质性,这为提升“城市矿产”的开发利用能力提供一定的决策参考。 The development and utilization of “urban minerals” is a complex process with multiple agents and multiple stages. This paper starts from five main agents and extracts thirty-five behavioral influence factors to construct a multi-agent collaborative evaluation index system for the development and utilization of urban minerals. To reflect the indicators’ relevance, based on the multi-agent collaborative questionnaire, the ANP is used to calculate the indicator weights, which are then used as the input of the BPNN model. The collaborative evaluation model is constructed by analyzing the BPNN model’s principle, and the training, testing, and verification of the BPNN are carried out with multiple sets of samples as the prior samples. It is found that social environment, environmental responsibility, transportation cost, recovery cost, and market environment are the key indicators that affect the multi-agent coordination of urban minerals, and there is heterogeneity in index weights of enterprises of different nature and sizes, which provides a certain decision-making reference for the development and utilization of urban minerals.
作者 陈丽强 高明 梁开荣 Chen Liqiang;Gao Ming;Liang Kairong(School of Economics and Management,Fuzhou University,Fuzhou 350108;Green Development Institute,Fuzhou University,Fuzhou 350108)
出处 《管理评论》 北大核心 2023年第2期16-27,共12页 Management Review
基金 国家社会科学基金项目(22BGL181)。
关键词 “城市矿产” 多主体协同 ANP-BPNN模型 关键因素 urban minerals multi-agent collaboration ANP-BPNN model key factors
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