机构

• 地理科学与资源研究... [12]
• 地球环境研究所 [12]
• 生态环境研究中心 [5]
• 广州生物医药与健康研... [2]
• 地质与地球物理研究所 [1]
• 上海药物研究所 [1]
• 更多

采集方式

• OAI收割 [38]

内容类型

• 期刊论文 [38]

发表日期

• 2023 [5]
• 2022 [7]
• 2021 [10]
• 2020 [2]
• 2019 [2]
• 2017 [2]
• 更多

学科主题

• Cell Biolo... [2]

筛选

浏览/检索结果: 共38条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择提交时间升序提交时间降序发表日期升序发表日期降序题名升序题名降序作者升序作者降序 Prediction of monthly average and extreme atmospheric temperatures in Zhengzhou based on artificial neural network and deep learning models 期刊论文  OAI收割 FRONTIERS IN FORESTS AND GLOBAL CHANGE, 2023, 卷号: 6, 页码: 1249300 作者:  Guo, Qingchun;  He, Zhenfang;  Wang, Zhaosheng   |  收藏  |  浏览/下载：5/0  |  提交时间：2024/01/04 extreme atmospheric temperature  artificial neural network  deep learning  CNN-GRU  CNN-LSTM  prediction  training algorithm  forest   Learning ensembles of process-based models for high accurately evaluating the one-hundred-year carbon sink potential of China's forest ecosystem 期刊论文  OAI收割 HELIYON, 2023, 卷号: 9, 期号: 6, 页码: e17243 作者:  Wang, Zhaosheng;  Li, Renqiang;  Guo, Qingchun;  Wang, Zhaojun;  Huang, Mei   |  收藏  |  浏览/下载：13/0  |  提交时间：2023/09/07 Learning ensembles of process-based models  Random forest model  Forest ecosystem  Carbon sink potential   Prediction of Hourly PM2.5 and PM10 Concentrations in Chongqing City in China Based on Artificial Neural Network 期刊论文  OAI收割 AEROSOL AND AIR QUALITY RESEARCH, 2023, 卷号: 23, 期号: 6, 页码: 11 作者:  Guo, Qingchun;  He, Zhenfang;  Wang, Zhaosheng   |  收藏  |  浏览/下载：5/0  |  提交时间：2023/10/09 Air pollution  Artificial neural network  Meteorological element  Predict  PM 2  5  PM 10  Chongqing  Training function   Change in Air Quality during 2014-2021 in Jinan City in China and Its Influencing Factors 期刊论文  OAI收割 TOXICS, 2023, 卷号: 11, 期号: 3, 页码: 210 作者:  Guo, Qingchun;  He, Zhenfang;  Wang, Zhaosheng   |  收藏  |  浏览/下载：3/0  |  提交时间：2024/01/04 air quality  influencing factors  PM2 5  PM10  COVID-19   Predicting of Daily PM2.5 Concentration Employing Wavelet Artificial Neural Networks Based on Meteorological Elements in Shanghai, China 期刊论文  OAI收割 TOXICS, 2023, 卷号: 11, 期号: 1, 页码: 19 作者:  Guo, Qingchun;  He, Zhenfang;  Wang, Zhaosheng   |  收藏  |  浏览/下载：10/0  |  提交时间：2023/03/20 PM2 5  wavelet  artificial neural network  predicting  DNN  CNN  LSTM  COVID-19  epidemic   Long-term projection of future climate change over the twenty-first century in the Sahara region in Africa under four Shared Socio-Economic Pathways scenarios 期刊论文  OAI收割 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 页码: 11 作者:  Guo, Qingchun;  He, Zhenfang   |  收藏  |  浏览/下载：21/0  |  提交时间：2022/11/18 Climate change  Sahara  Shared Socio-Economic Pathways  Future  Greenhouse gas   Long-term projection of future climate change over the twenty-first century in the Sahara region in Africa under four Shared Socio-Economic Pathways scenarios 期刊论文  OAI收割 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 页码: 11 作者:  Guo, Qingchun;  He, Zhenfang;  Wang, Zhaosheng   |  收藏  |  浏览/下载：19/0  |  提交时间：2022/11/18 Climate change  Sahara  Shared Socio-Economic Pathways  Future  Greenhouse gas   Prediction of Monthly PM2.5 Concentration in Liaocheng in China Employing Artificial Neural Network 期刊论文  OAI收割 ATMOSPHERE, 2022, 卷号: 13, 期号: 8, 页码: 16 作者:  He, Zhenfang;  Guo, Qingchun;  Wang, Zhaosheng;  Li, Xinzhou   |  收藏  |  浏览/下载：26/0  |  提交时间：2022/09/26 air pollution  artificial intelligence  COVID-19  deep learning  long short-term memory   Prediction of Monthly PM2.5 Concentration in Liaocheng in China Employing Artificial Neural Network 期刊论文  OAI收割 ATMOSPHERE, 2022, 卷号: 13, 期号: 8, 页码: 1221 作者:  He, Zhenfang;  Guo, Qingchun;  Wang, Zhaosheng;  Li, Xinzhou   |  收藏  |  浏览/下载：11/0  |  提交时间：2022/11/07 Fabrication of magnetically responsive anti-fouling and easy-cleaning nanofiber membrane and its application for efficient oil-water emulsion separation 期刊论文  OAI收割 CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2022, 卷号: 41, 页码: 286-293 作者:  Wang, Yajie;  Guo, Zhiwei   |  收藏  |  浏览/下载：48/0  |  提交时间：2022/06/15 Superparamagnetic  Nanofiber membrane  Anti-fouling  Oil-water emulsion  Regeneration