文章基于CiteSpace软件和Web of Science核心数据库,对国外基于自然的解决方案(NbS)文献进行梳理和分析,以期为该领域研究及其在中国本土化的应用提供参考。结果表明:1)国外NbS研究处于快速发展阶段,2016年后发文量显著提升,研究集中分...文章基于CiteSpace软件和Web of Science核心数据库,对国外基于自然的解决方案(NbS)文献进行梳理和分析,以期为该领域研究及其在中国本土化的应用提供参考。结果表明:1)国外NbS研究处于快速发展阶段,2016年后发文量显著提升,研究集中分布在北美、欧洲等地区,欧盟国家汇集了主要的研究机构,但尚未出现具有影响力的学者;2)NbS的知识研究基础以评估框架研究和实践案例研究为主;3)NbS研究5大热点为城市再生、绿色空间管理、气候适应与变化减缓、海岸韧性以及参与式规划和治理,该领域早期聚焦于与之相关的概念研究,而后转向具体方向领域的实证研究;4)NbS研究重点为蓝绿基础设施建设、生态系统恢复以及海岸灾害防御3大领域。在此基础上,对NbS研究提出展望,即未来应重视概念辨析、加强实证研究、注重利益相关者间权衡,以及促进在发展中国家推广。展开更多
Detection of floating garbage in inland rivers is crucial for water environmental protection,as it effectively reduces ecological damage and ensures the safety of water resources.To address the inefficiency of traditi...Detection of floating garbage in inland rivers is crucial for water environmental protection,as it effectively reduces ecological damage and ensures the safety of water resources.To address the inefficiency of traditional cleanup methods and the challenges in detecting small targets,an improved YOLOv5 object detection model was proposed in this study.In order to enhance the model’s sensitivity to small targets and mitigate the impact of redundant information on detection performance,a bi-level routing attention mechanism was introduced and embedded into the backbone network.Additionally,a multi-scale detection head was incorporated into the model,allowing for more comprehensive coverage of floating garbage of various sizes through multi-scale feature extraction and detection.The Focal-EIoU loss function was also employed to optimize the model parameters,improving localization accuracy.Experimental results on the publicly available FloW_Img dataset demonstrated that the improved YOLOv5 model outperforms the original YOLOv5 model in terms of precision and recall,achieving a mAP(mean average precision)of 86.12%,with significant improvements and faster convergence.展开更多
文摘文章基于CiteSpace软件和Web of Science核心数据库,对国外基于自然的解决方案(NbS)文献进行梳理和分析,以期为该领域研究及其在中国本土化的应用提供参考。结果表明:1)国外NbS研究处于快速发展阶段,2016年后发文量显著提升,研究集中分布在北美、欧洲等地区,欧盟国家汇集了主要的研究机构,但尚未出现具有影响力的学者;2)NbS的知识研究基础以评估框架研究和实践案例研究为主;3)NbS研究5大热点为城市再生、绿色空间管理、气候适应与变化减缓、海岸韧性以及参与式规划和治理,该领域早期聚焦于与之相关的概念研究,而后转向具体方向领域的实证研究;4)NbS研究重点为蓝绿基础设施建设、生态系统恢复以及海岸灾害防御3大领域。在此基础上,对NbS研究提出展望,即未来应重视概念辨析、加强实证研究、注重利益相关者间权衡,以及促进在发展中国家推广。
文摘Detection of floating garbage in inland rivers is crucial for water environmental protection,as it effectively reduces ecological damage and ensures the safety of water resources.To address the inefficiency of traditional cleanup methods and the challenges in detecting small targets,an improved YOLOv5 object detection model was proposed in this study.In order to enhance the model’s sensitivity to small targets and mitigate the impact of redundant information on detection performance,a bi-level routing attention mechanism was introduced and embedded into the backbone network.Additionally,a multi-scale detection head was incorporated into the model,allowing for more comprehensive coverage of floating garbage of various sizes through multi-scale feature extraction and detection.The Focal-EIoU loss function was also employed to optimize the model parameters,improving localization accuracy.Experimental results on the publicly available FloW_Img dataset demonstrated that the improved YOLOv5 model outperforms the original YOLOv5 model in terms of precision and recall,achieving a mAP(mean average precision)of 86.12%,with significant improvements and faster convergence.
