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浏览/检索结果: 共102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发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Defects-Induced Fatigue Failure Behavior and Life Prediction of Laser Powder Bed Fusion GH4169 Superalloy in High and Very-High Cycle Regimes 期刊论文  OAI收割 ADVANCED ENGINEERING MATERIALS, 2025, 页码: 17 作者:  Mahmood, Asif;  Sun, Chuanwen;  Li, Wei;  Li C(李成);  Lashari, Muhammad Imran   |  收藏  |  浏览/下载：11/0  |  提交时间：2025/09/15 defect-induced fatigue life predictions  fatigue fracture behavior  laser powder bed fusions  solution aging  very-high cycle fatigue   Selective recruitment of core rhizobacterial communities with distinct life-history strategies by two grass genera 期刊论文  OAI收割 JOURNAL OF PLANT ECOLOGY, 2025, 卷号: 18, 期号: 6 作者:  Wang, Yingcheng;  Wang, Junbang;  Wu, Chu;  Zhou, Huakun;  Zhang, Miao   |  收藏  |  浏览/下载：18/0  |  提交时间：2025/11/27 core rhizobacteria  dominant grass  functional predictions  r/K-selection theory  Qinghai-Tibetan Plateau region   Guest Editorial of Virtual Special Issue: Artificial Intelligence-Assisted Fatigue Prediction of Engineering Materials and Structures 期刊论文  OAI收割 FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES, 2024 作者:  Xin, Haohui;  Qian GA(钱桂安);  Correia, Jose Antonio;  Berto, Filippo;  Zhang, Youyou   |  收藏  |  浏览/下载：35/0  |  提交时间：2024/12/02 AI-assisted fatigue crack growth  AI-assisted fatigue damage prediction  AI-assisted fatigue life predictions   ENSO-Related Precursor Pathways of Interannual Thermal Anomalies Identified Using a Transformer-Based Deep Learning Model in the Tropical Pacific 期刊论文  OAI收割 GEOPHYSICAL RESEARCH LETTERS, 2024, 卷号: 51, 期号: 12, 页码: 11 作者:  Zhou, Lu   |  收藏  |  浏览/下载：50/0  |  提交时间：2024/09/02 ENSO predictions  thermal precursors  multivariate three-dimensional (3D) predictions  transformer-based model  explainable artificial intelligence (XAI)   Machine learning-assisted structure annotation of natural products based on MS and NMR data 期刊论文  OAI收割 NATURAL PRODUCT REPORTS, 2023, 卷号: 40, 期号: 11, 页码: 1735-1753 作者:  Hu,Guilin;  Qiu,Minghua   |  收藏  |  浏览/下载：18/0  |  提交时间：2024/07/10 H-1-NMR CHEMICAL-SHIFTS  STRUCTURE-BASED PREDICTIONS  TANDEM MASS-SPECTRA  STRUCTURE ELUCIDATION  NEURAL-NETWORK  METABOLITE IDENTIFICATION  COMP   Multi-model driven by diverse precipitation datasets increases confidence in identifying dominant factors for runoff change in a subbasin of the Qaidam Basin of China 期刊论文  OAI收割 SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 卷号: 802, 页码: 12 作者:  Lv, Aifeng;  Qi, Shanshan;  Wang, Gangsheng   |  收藏  |  浏览/下载：76/0  |  提交时间：2021/11/05 Inland basin  Climatic variation  Human activities  Precipitation products  Predictions in ungauged basins (PUBs)  SWAT   The solution to the '1/2 vs 3/2' puzzle 期刊论文  OAI收割 EUROPEAN PHYSICAL JOURNAL C, 2022, 卷号: 82, 期号: 11, 页码: 1027 作者:  Wang, Guo-Li;  Li, Qiang;  Wang, Tianhong;  Feng, Tai-Fu;  Wu, Xing-Gang   |  收藏  |  浏览/下载：60/0  |  提交时间：2023/01/16 SEMILEPTONIC B DECAYS  D-ASTERISK-ASTERISK  MESONS  TAU  PREDICTIONS  TRANSITIONS  CONSTANTS  MODEL   Multi-model driven by diverse precipitation datasets increases confidence in identifying dominant factors for runoff change in a subbasin of the Qaidam Basin of China 期刊论文  OAI收割 SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 卷号: 802, 页码: 12 作者:  Lv, Aifeng;  Qi, Shanshan;  Wang, Gangsheng   |  收藏  |  浏览/下载：56/0  |  提交时间：2021/11/05 Inland basin  Climatic variation  Human activities  Precipitation products  Predictions in ungauged basins (PUBs)  SWAT   A discrete-time and finite-state Markov chain based in-play prediction model for NBA basketball matches 期刊论文  OAI收割 COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2021, 卷号: 50, 期号: 11, 页码: 3768-3776 作者:  Shi, Jian;  Song, Kai   |  收藏  |  浏览/下载：50/0  |  提交时间：2022/04/02 Betting  In-play predictions  Markov chain  Positive returns  Uncertainty analysis   Disruption prediction on EAST tokamak using a deep learning algorithm 期刊论文  OAI收割 Plasma Physics and Controlled Fusion, 2021, 卷号: 63 作者:  Guo,B H;  Chen,D L;  Shen,B;  Rea,C;  Granetz,R S   |  收藏  |  浏览/下载：59/0  |  提交时间：2021/11/01 disruptions  predictions  EAST  tokamak  deep learning