机构

• 自动化研究所 [21]
• 地理科学与资源研究... [15]
• 计算技术研究所 [13]
• 武汉岩土力学研究所 [8]
• 力学研究所 [6]
• 沈阳自动化研究所 [6]
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• OAI收割 [110]

内容类型

• 期刊论文 [106]
• 学位论文 [3]
• 会议论文 [1]

发表日期

• 2026 [5]
• 2025 [9]
• 2024 [14]
• 2023 [16]
• 2022 [14]
• 2021 [21]
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学科主题

• Engineerin... [3]
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浏览/检索结果: 共110条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择作者升序作者降序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 Prioritizing climate action maximizes synergies among global environmental SDGs: A causal network analysis 期刊论文  OAI收割 APPLIED GEOGRAPHY, 2026, 卷号: 189, 页码: 103938 作者:  Huan, Yizhong;  Wu, Fei;  Li, Xiaoyun;  Wang, Jing;  Su, Yiming   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/03/16 Sustainable development  Environmental governance  Causal interaction  Network analysis  Machine learning  Resilience   Divergent responses of soil organic carbon stocks in different layers to global changes on the Tibetan Plateau 期刊论文  OAI收割 CATENA, 2026, 卷号: 265, 页码: 16 作者:  Zhang, Xin;  Chen, Hongjin;  Zhou, Jun;  Zhang, Xiyu;  Fan, Jianrong   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/03/31 Climate change  Machine learning  Spatial analysis  Environmental factors  Soil layer.   Enhancing Landslide Susceptibility and Dynamic Exposure Assessment Using Interpretable Machine Learning: A Case Study of the Qinba Mountain Area, China 期刊论文  OAI收割 TRANSACTIONS IN GIS, 2026, 卷号: 30, 期号: 2, 页码: e70228 作者:  Shi, Yi;  Lin, Qigen;  Hong, Haoyuan   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/04/16 Dynamic exposure analysis  Interpretable machine learning  Landslide risk mapping  Landslide Susceptibility mapping   Landslide Susceptibility Assessment Based on TFPF-SU and AuFNN Methods: A Case Study of Dongchuan District, Yunnan Province 期刊论文  OAI收割 APPLIED SCIENCES-BASEL, 2026, 卷号: 16, 期号: 2, 页码: 1035 作者:  Li, Kuan;  Sun, Yuqiang;  Fan, Junfu;  Li, Ping   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/03/16 slope unit  landslide  evaluation factors  susceptibility analysis  machine learning   Capturing spatio-temporal variations in SDG interactions and prioritizations 期刊论文  OAI收割 APPLIED GEOGRAPHY, 2026, 卷号: 186, 页码: 103830 作者:  Huan, Yizhong;  Li, Xiaoyun;  Li, Pengfei;  Li, Xin;  Lan, Yang   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/04/16 Sustainable development  Spatio-temporal variations  Network analysis  Machine learning  SDG interactions  Global governance   Study on the spatiotemporal variation mechanisms of soil moisture in maize fields 期刊论文  OAI收割 SCIENTIFIC REPORTS, 2025, 卷号: 16, 期号: 1, 页码: 2434 作者:  Lan, Lihua;  Zhang, Tingting;  Wang, Baolin;  He, Fei;  Wu, Xiaoyong   |  收藏  |  浏览/下载：0/0  |  提交时间：2026/02/09 Soil moisture variability  Phenological stages of maize  Environmental indicators  Radar-based modeling  Machine learning analysis   Characterizing and clustering debris flow and environmental noise seismic signals using unsupervised deep learning 期刊论文  OAI收割 GEOPHYSICAL JOURNAL INTERNATIONAL, 2025, 卷号: 243, 期号: 2, 页码: 18 作者:  Huang, Zhiyong;  Yang, Zongji;  Pang, Bo;  Wu, Zhaoying;  Feng, Liang   |  收藏  |  浏览/下载：1/0  |  提交时间：2025/11/06 Machine learning  Time-series analysis  Computational seismology  Seismic noise  Statistical seismology   Assessing relative contributions of climate and socio-environmental factors to ecosystem health through space-time interpretable machine learning 期刊论文  OAI收割 ECOLOGICAL INDICATORS, 2025, 卷号: 178, 页码: 114087 作者:  Meng, Xiaoliang;  Wu, Junyi;  Xie, Yichun;  Bai, Yongfei;  Zhou, Chenghu   |  收藏  |  浏览/下载：0/0  |  提交时间：2025/11/17 Relative contributions of coupled climate and  socioenvironmental factors  Interpretable machine learning  Fine-grained spatial and temporal analysis  Each feature's contribution to individual  prediction (EFCTIP)  Localized EFCTIP   Distinguishing dominant drivers on long-term vegetation dynamics across China considering time-lag and accumulation effects using machine learning techniques 期刊论文  OAI收割 JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2025, 卷号: 391, 页码: 126477 作者:  Wang, Qianxin;  Huang, Lin;  Yang, Meng;  Wang, Lan;  Cao, Wei   |  收藏  |  浏览/下载：1/0  |  提交时间：2025/09/22 Long-term vegetation dynamics  Time-lag and accumulation effects  Attribution analysis  Machine learning  China   Optimizing Cu2+adsorption prediction in Undaria pinnatifida using machine learning and isotherm models 期刊论文  OAI收割 JOURNAL OF HAZARDOUS MATERIALS, 2025, 卷号: 492, 页码: 13 作者:  Chen, Haoran;  Zhang, Rui;  Qu, Xiaohan;  Shan, Tifeng;  Wang, Yuhe   |  收藏  |  浏览/下载：33/0  |  提交时间：2025/07/11 Heavy metal removal  Machine learning  Traditional adsorption models  Bioactive materials  Explainable analysis