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浏览/检索结果: 共1215条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择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发表日期升序发表日期降序 Spatiotemporal patterns and drivers of public concern about air pollution in China: Leveraging online big data and interpretable machine learning 期刊论文  OAI收割 ENVIRONMENTAL IMPACT ASSESSMENT REVIEW, 2025, 卷号: 114, 页码: 107897 作者:  Xu, Gang;  Liu, Haimeng;  Jia, Chunwang;  Zhou, Tianyu;  Shang, Jing   |  收藏  |  浏览/下载：7/0  |  提交时间：2025/04/21 Public environmental concern  Air quality  Environmental perception  Machine learning  XGBoost-SHAP  Environmental assessment  Environmental governance   Multi-resolution reconstruction of longitudinal streambed footprints using embedded sparse convolutional autoencoders 期刊论文  OAI收割 JOURNAL OF HYDROLOGY, 2025, 卷号: 654, 页码: 18 作者:  Yang, Yifan;  Tang, Zihao;  Shao D(邵东);  Xu, Zhonghou   |  收藏  |  浏览/下载：3/0  |  提交时间：2025/03/21 Machine learning  Streambed footprint  Convolutional autoencoder  Multi-resolution reconstruction   Chat-microreactor: A large-language-model-based assistant for designing continuous flow systems 期刊论文  OAI收割 CHEMICAL ENGINEERING SCIENCE, 2025, 卷号: 311 作者:  Pan, Yongqi;  Xiao, Qinfan;  Zhao, Fangyu;  Li ZH(李振豪);  Liu, Jianyang   |  收藏  |  浏览/下载：18/0  |  提交时间：2025/04/21 Flow chemistry  Microreactor  Large language models  Machine learning  Multi-phase dispersion   Selecting suitable sites for livestock manure composting via the integration of machine learning, median center and geographic information system 期刊论文  OAI收割 AGRICULTURAL SYSTEMS, 2025, 卷号: 226, 页码: 104300 作者:  Yan, Jingjie;  Yan, Bojie;  Shi, Wenjiao;  Feng, Yulin   |  收藏  |  浏览/下载：8/0  |  提交时间：2025/04/21 Livestock manure  Spatial clusters  Machine learning  Suitable sites   Mapping cropland soil salinity using multi-cycle classification to mitigate retrieval errors 期刊论文  OAI收割 COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2025, 卷号: 231, 页码: 110055 作者:  Gao, Liaoran;  Xu, Erqi   |  收藏  |  浏览/下载：8/0  |  提交时间：2025/03/18 Soil salinization  Remote sensing  Multi-cycle classification  Machine learning   Assessing and predicting Bojiang lake area and LULC changes from 2000 to 2045 期刊论文  OAI收割 JOURNAL OF HYDROLOGY-REGIONAL STUDIES, 2025, 卷号: 58, 页码: 102216 作者:  Naeem, Muhammad;  Zhang, Yongqiang;  Tian, Xiaoqiang;  Miao, Ping;  Li, Congcong   |  收藏  |  浏览/下载：4/0  |  提交时间：2025/03/18 Machine Learning  CA-ANN Model  Lake changes  Land Use and Land Cover (LULC) Changes  Climate Change  Water management   Comparison and integration of hydrological models and machine learning models in global monthly streamflow simulation 期刊论文  OAI收割 JOURNAL OF HYDROLOGY, 2025, 卷号: 650, 页码: 17 作者:  Zhang, Jiawen;  Kong, Dongdong;  Li, Jianfeng;  Qiu, Jianxiu;  Zhang, Yongqiang   |  收藏  |  浏览/下载：7/0  |  提交时间：2025/03/31 Streamflow simulation  Machine learning  Hydrological model  Multi-model weighting ensemble   A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics 期刊论文  OAI收割 JOURNAL OF CHROMATOGRAPHY A, 2025, 卷号: 1745, 页码: 12 作者:  Huang, Yu-shi;  An, Ya-ling;  Zheng, Yue-yuan;  Zhao, Wen-jie;  Song, Chun-qian   |  收藏  |  浏览/下载：12/0  |  提交时间：2025/04/01 Citrus herbs  Discrimination  LC-MS  Machine learning  Differential markers   The Evolution of Global Surface Ammonia Concentrations during 2001-2019: Magnitudes, Patterns, and Drivers 期刊论文  OAI收割 ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2025, 卷号: 59, 期号: 10, 页码: 5066-5079 作者:  Ma, Jiageng;  Shi, Hao;  Zhu, Yingjie;  Li, Rui;  Wang, Shaoqiang   |  收藏  |  浏览/下载：9/0  |  提交时间：2025/04/21 global surface ammonia concentration  Box-Cox transformation  scale-adaptive rotating quadtree  machine learning  nitrogen fertilizer application   Machine learning-driven analysis of greenhouse gas emissions from rice production in major Chinese provinces: Identifying key factors and developing reduction strategies 期刊论文  OAI收割 EUROPEAN JOURNAL OF AGRONOMY, 2025, 卷号: 164, 页码: 127536 作者:  Huan, Songhua;  Liu, Xiuli   |  收藏  |  浏览/下载：10/0  |  提交时间：2025/03/18 Rice production  Greenhouse gas emission intensity  Machine learning models  Driving factors  Reduction strategies