摘要
资源环境承载力体现了港口资源环境对相关社会经济活动的支撑能力。剖析港口资源环境承载力的内涵和维度有助于优化港口资源利用、加强港口生态环境保护、促进港口与区域社会经济可持续发展。基于此,本研究从资源、社会经济和环境三个角度构建港口资源环境承载力评价指标体系,并制定四级分级标准,采用遗传神经网络评价模型对各子系统承载力水平进行评价,并运用耦合协调度模型分析了子系统之间的耦合协调发展水平,同时利用自回归分布滞后模型进一步探究了各子系统对港口资源环境承载力的影响。为验证上述模型的有效性,本研究以2013-2022年宁波舟山港宁波港域的数据为例进行了数值分析。结果显示:近10年间该港域的资源环境承载力总体呈上升趋势,2018-2022年处于次理想承载状态,且子系统之间耦合协调度处于较高水平且发展趋势良好。鉴于该评价结果与实际情况基本相符,由此证明该评价方法有效且适用,可为港口的可持续发展提供具有实践意义的理论支撑。
The resource and environmental carrying capacity reflects the ports’capability to support relevant socio-economic activities.Study on its connotation and dimension may optimize utilization of port resources,enhance ecological environmental protection,and promote sustainable development of ports and regional socio-economies.Based on the analysis,this study constructs a corresponding evaluation index system in terms of resources,socio-economics and the environment with a four-level grading standard.A genetic neural network evaluation model is employed to assess the carrying capacity levels of various subsystems.Furthermore,a coupling coordination degree model(CCDM)is applied to analyze the coupling coordination development levels among subsystems,and an autoregressive distributed lag model is adopted to further explore the impact of each subsystem on the carrying capacity of the port resource and environmental carrying capacity.To validate the feasibility of the methods,numerical analysis is made based on data from the Ningbo-Zhoushan Port of the Ningbo port area between 2013 and 2022.The results indicate that over the past decade,the resource and environmental carrying capacity of the Ningbo port area has generally increased,reaching a near-ideal state from 2018 till 2022 and the coupling coordination degree among subsystems is at a high level with a positive development trend.As the results approximate the actual situation,it is verified that the assessment method is effective and applicable,providing practical theoretical support for the sustainable development of ports.
作者
周炜翔
ZHOU Weixiang(Ningbo University,Ningbo,Zhejiang 315832,China)
出处
《物流技术》
2025年第5期73-84,共12页
Logistics Technology
基金
国家自然科学基金项目(52272334)。
关键词
港口
资源环境承载力
系统耦合
遗传神经网络
自回归分布滞后模型
port
resource and environmental carrying capacity
system coupling
GA-BP neutral network
autoregressive distributed lag model
