机构

• 地理科学与资源研究所 [1]
• 长春光学精密机械与物... [1]
• 数学与系统科学研究院 [1]
• 上海药物研究所 [1]

采集方式

• OAI收割 [4]

内容类型

• 期刊论文 [3]
• 会议论文 [1]

发表日期

• 2024 [1]
• 2018 [1]
• 2010 [1]
• 2009 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4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 Predicting Flood Event Class Using a Novel Class Membership Function and Hydrological Modeling 期刊论文  OAI收割 EARTHS FUTURE, 2024, 卷号: 12, 期号: 6, 页码: e2023EF004081 作者:  Zhang, Yongyong;  Zhang, Yongqiang;  Zhai, Xiaoyan;  Xia, Jun;  Tang, Qiuhong   |  收藏  |  浏览/下载：20/0  |  提交时间：2024/07/12 flood event class  class membership function  hit rate  flood regime metrics  catchment hydrological model   A model averaging approach for the ordered probit and nested logit models with applications 期刊论文  OAI收割 JOURNAL OF APPLIED STATISTICS, 2018, 卷号: 45, 期号: 16, 页码: 3012-3052 作者:  Chen, Longmei;  Wan, Alan T. K.;  Tso, Geoffrey;  Zhang, Xinyu   |  收藏  |  浏览/下载：158/0  |  提交时间：2018/11/16 Hit rate  model averaging  model selection  Monte Carlo  nested logit  ordered probit  screening   Prediction model of molten iron endpoint temperature in AOD furnace based on RBF neural network (EI CONFERENCE) 会议论文  OAI收割 2010 International Conference on Logistics Systems and Intelligent Management, ICLSIM 2010, January 9, 2010 - January 10, 2010, Harbin, China Ma H.-T.; You W.; Chen T. 收藏  |  浏览/下载：29/0  |  提交时间：2013/03/25 According to Jilin Ferroalloy Factory 10-ton AOD furnace actual smelting condition  analyzes the impact factor of AOD furnace molten iron endpoint temperature  by optimizing the neural network connection weights and structure  design prediction model of molten iron endpoint temperature based on RBF neural network  using LM algorithm and 50 furnaces actual production data to train the model  and predicts another 50 furnaces molten iron temperature  Result shows that prediction model of molten iron endpoint temperature based on RBF neural network has a high accuracy  when the error of endpoint temperature is 12 C  hit rate of temperature is 82.4%. 2010 IEEE.   Pharmacophore-based virtual screening versus docking-based virtual screening: a benchmark comparison against eight targets 期刊论文  OAI收割 ACTA PHARMACOLOGICA SINICA, 2009, 卷号: 30, 期号: 12, 页码: 1694-1708 作者:  Chen, Zhi;  Li, Hong-lin;  Zhang, Qi-jun;  Bao, Xiao-guang;  Yu, Kun-qian   |  收藏  |  浏览/下载：24/0  |  提交时间：2019/01/08 pharmacophore  docking  LigandScout  enrichment  hit rate