农业资源与环境学报2025，Vol.42Issue(6)：1679-1686,8.DOI:10.13254/j.jare.2024.0837
基于人工神经网络模型的沧州市水生态承载力评估
Assessment of water ecological carrying capacity in Cangzhou City based on artificial neural network model
摘要
Abstract
The study of water ecological carrying capacity can be used as an effective approach to predict the problems arising in sustainable development from the perspective of water ecology.The traditional quantitative process of water ecological carrying capacity is complicated due to the index concept inconformity and multi-field intersection.In this study,the quantitative evaluation model of water ecological carrying capacity was established by constructing the index system of water resources,water environment,water ecology and water security,and combining the structure and characteristics of artificial neural network,which provides a scientific method for the calculation of water ecological carrying capacity.Moreover,taking Cangzhou City,a typical eco-water-deficient city,as an example,the calculations showed that from 2015 to 2019 the indexes of water ecological carrying capacity were 0.26,0.23,0.23,0.24 and 0.22,respectively.It reflected that the overall ecological carrying capacity was at a loaded state,barely meeting the standard level,which may threaten the green,healthy,and sustainable development of the ecological environment.It can be seen that the combination of the index system and neural network model has the advantages of simple structure,strong anti-interference ability and more intuitive results,so that the regional carrying capacity state can be presented more intuitively and effectively,providing help for the solution of water ecological problems in this region and the designation for future development direction.关键词
水生态承载力/指标体系/人工神经网络/沧州市Key words
water ecological carrying capacity/index system/artificial neural network/Cangzhou City引用本文复制引用
郑浩巍,王焕华,卢少勇,贾建丽,万正芬,毕斌,张森霖..基于人工神经网络模型的沧州市水生态承载力评估[J].农业资源与环境学报,2025,42(6):1679-1686,8.基金项目
沧州市水环境质量改善技术服务项目 Project of Cangzhou with Technical Services for Improving Water Environment Quality （）
