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浏览/检索结果: 共113条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择发表日期升序发表日期降序题名升序题名降序提交时间升序提交时间降序作者升序作者降序 Revealing the transfer and impacts of ecological footprint embodied in interprovincial trade across China's metacoupled system 期刊论文  OAI收割 ENVIRONMENTAL IMPACT ASSESSMENT REVIEW, 2026, 卷号: 118, 页码: 108329 作者:  Zhang, Ruqian;  Li, Penghui;  Kong, Xiangbin;  Zhong, Shuai   |  收藏  |  浏览/下载：6/0  |  提交时间：2026/02/09 Ecological footprint transfer  Metacoupling framework  Interprovincial trade  Multi-regional input-output  Trade scenarios   Characteristics and key drivers of virtual urban land flows in China 期刊论文  OAI收割 LAND USE POLICY, 2026, 卷号: 163, 页码: 107923 作者:  Liu, Haimeng;  Xiong, Jieyang;  Song, Tao   |  收藏  |  浏览/下载：8/0  |  提交时间：2026/02/09 Virtual urban built-up land  Environmental footprint  Urbanization  Urban sustainable development  Telecoupling  Environment-extended multi-region input-output model   Global-Local Linkage Patterns of Guangdong's Industries: Evidence from Multi-Scale Input-Output Network Analysis 期刊论文  OAI收割 SYSTEMS, 2026, 卷号: 14, 期号: 3, 页码: 272 作者:  Mao, Lingxiao;  Liu, Yi;  Qian, Xiaoying;  Zhang, Weishi;  Zhang, Chaoyu   |  收藏  |  浏览/下载：2/0  |  提交时间：2026/05/22 input-output analysis  global-local interaction  multi-scale nesting  industrial linkage path  foreign trade gateway   A comparative study of CO2 emissions from provincial transportation industry before and after COVID-19 in China 期刊论文  OAI收割 ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2026, 卷号: N/A 作者:  He, Yi-jing;  Wen, Wen;  Zhang, Xing-man;  Su, Yang;  Gao, Xing   |  收藏  |  浏览/下载：6/0  |  提交时间：2026/02/09 COVID-19  Transportation  Multi-Regional Input-Output model (MRIO)  Carbon emissions  Structural path analysis (SPA)   Estimating multi-source input uncertainties and their propagation for integrated water quantity and quality simulations 期刊论文  OAI收割 HYDROLOGICAL SCIENCES JOURNAL, 2025, 卷号: N/A 作者:  Han, Bing;  Zhang, Yongyong;  Shao, Quanxi;  Duan, Qingyun;  Gebremedhn, Abrha Ybeyn   |  收藏  |  浏览/下载：3/0  |  提交时间：2025/12/19 Multi-source input uncertainties  propagated uncertainty  integrated water system simulations   Recontextualizing Telecouplings in Electricity-Driven Land Use Flows via Global Supply Chains 期刊论文  OAI收割 LAND, 2025, 卷号: 14, 期号: 11, 页码: 2150 作者:  Li, Xiao;  Li, Chaohui;  Gill, Muhammad Yasin;  Han, Mengyao;  Liu, Yihong   |  收藏  |  浏览/下载：7/0  |  提交时间：2026/01/21 multi-regional input-output analysis  embodied land  international trade  electricity-driven  renewable energy   Modeling spatial processes of extreme heat impacts on global economy: a multi-scale spatio-temporal approach 期刊论文  OAI收割 SCIENCE BULLETIN, 2025, 卷号: 70, 期号: 19, 页码: 3233-3244 作者:  Dong, Guanpeng;  Zhang, Hang;  Liu, Yansui;  Miao, Changhong   |  收藏  |  浏览/下载：3/0  |  提交时间：2025/11/17 Spatial statistics  Multi-scale model  Spatial autocorrelation  Extreme heat  Input-output   Runoff Forecast Model Integrating Time Series Decomposition and Deep Learning for the Short Term: A Case Study in the Weihe River Basin, China 期刊论文  OAI收割 WATER, 2025, 卷号: 17, 期号: 18, 页码: 2718 作者:  Ma, Ruijia;  An, Qiang;  Liu, Liu;  Cheng, Yongming;  Liu, Xingcai   |  收藏  |  浏览/下载：5/0  |  提交时间：2025/11/17 runoff forecasting  Convolutional Long Short-Term Memory  Seasonal-Trend decomposition using Loess  Variational Mode Decomposition  segmented decomposition sampling  multi-input neural network   Regional differences and transfer characteristics of global industrial trade-embodied carbon emissions 期刊论文  OAI收割 ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2025, 卷号: N/A 作者:  Wang, Guofeng;  Qing, Lu;  Guo, Qinyang;  Zhao, Baohui;  Du, Yiqiong   |  收藏  |  浏览/下载：7/0  |  提交时间：2025/10/20 Global industrial trade  Embodied carbon emission  Transfer characteristics  Multi-regional input-output model   Deep-Learning-Based Amplitude Variation with Angle Inversion with Multi-Input Neural Networks 期刊论文  OAI收割 PROCESSES, 2024, 卷号: 12, 期号: 10, 页码: 24 作者:  Tao, Shiping;  Guo, Yintong;  Huang, Haoyong;  Li, Junfeng;  Chen, Liqing   |  收藏  |  浏览/下载：34/0  |  提交时间：2025/06/27 pre-stack seismic inversion  deep learning method  multi-input  strong robustness  transfer learning