QQ客服 官方微博 反馈留言

浏览/检索结果: 共5条，第1-5条 帮助 限定条件 发表日期：2021     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Improving terrestrial evapotranspiration estimation across China during 2000-2018 with machine learning methods 期刊论文 JOURNAL OF HYDROLOGY, 2021, 卷号: 600, 页码: 18 作者:  Yin, Lichang;  Tao, Fulu;  Chen, Yi;  Liu, Fengshan;  Hu, Jian 收藏  |  浏览/下载：58/0  |  提交时间：2021/11/05 Evapotranspiration  Machine learning  process-based ET  ET integration  China  Gaussian process regression   The Two Formyl Peptide Receptors Differently Regulate GPR84-Mediated Neutrophil NADPH Oxidase Activity 期刊论文 JOURNAL OF INNATE IMMUNITY, 2021, 页码: 15 作者:  Martensson, Jonas;  Sundqvist, Martina;  Manandhar, Asmita;  Leremias, Loukas;  Zhang, Linjie 收藏  |  浏览/下载：42/0  |  提交时间：2021/05/24 Neutrophils  G protein-coupled receptors  Cross-talk  Nicotine adenine dinucleotide phosphate oxidase   Speed and Accuracy Tradeoff for LiDAR Data Based Road Boundary Detection 期刊论文 IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 6, 页码: 1210-1220 作者:  Guojun Wang;  Jian Wu;  Rui He;  Bin Tian 收藏  |  浏览/下载：14/0  |  提交时间：2021/06/11 3D-LiDAR  autonomous vehicle  object detection  point cloud  road boundary   Inter-comparison of several soil moisture downscaling methods over the Qinghai-Tibet Plateau, China 期刊论文 JOURNAL OF HYDROLOGY, 2021, 卷号: 592, 页码: 21 作者:  Qu, Yuquan;  Zhu, Zhongli;  Montzka, Carsten;  Chai, Linna;  Liu, Shaomin 收藏  |  浏览/下载：26/0  |  提交时间：2021/07/09 Soil moisture  Downscaling  Methods comparison  Qinghai-Tibet plateau   A comparative study of Gaussian process regression with other three machine learning approaches in the performance prediction of centrifugal pump 期刊论文 PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2021, 卷号: 236, 期号: 8, 页码: 3938-3949 作者:  Zhao, Xutao;  Zhang, Desheng;  Zhang, Renhui;  Xu, Bin 收藏  |  浏览/下载：13/0  |  提交时间：2022/03/01 Centrifugal pump  impeller parameters  performance prediction  machine learning  Gaussian process regression