机构

• 数学与系统科学研究院 [4]
• 科技战略咨询研究院 [1]

采集方式

• OAI收割 [5]

内容类型

• 期刊论文 [5]

发表日期

• 2022 [1]
• 2021 [1]
• 2018 [1]
• 2012 [1]
• 2008 [1]

学科主题

• Chemical [1]
• Energy & F... [1]

筛选

浏览/检索结果: 共5条，第1-5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 A new PM2.5 concentration forecasting system based on AdaBoost-ensemble system with deep learning approach 期刊论文  OAI收割 JOURNAL OF FORECASTING, 2022, 页码: 22 作者:  Li, Zhongfei;  Gan, Kai;  Sun, Shaolong;  Wang, Shouyang   |  收藏  |  浏览/下载：23/0  |  提交时间：2023/02/07 AdaBoost-ensemble  deep learning  hybrid data preprocessing-analysis strategy  LSTM   An innovative ensemble learning air pollution early-warning system for China based on incremental extreme learning machine 期刊论文  OAI收割 ATMOSPHERIC POLLUTION RESEARCH, 2021, 卷号: 12, 期号: 9, 页码: 15 作者:  Du, Zongjuan;  Heng, Jiani;  Niu, Mingfei;  Sun, Shaolong   |  收藏  |  浏览/下载：36/0  |  提交时间：2022/04/02 Air quality early-warning system  Length-changeable incremental extreme  learning machine  Hybrid ensemble model  Fuzzy evaluation   A secondary-decomposition-ensemble learning paradigm for forecasting PM2.5 concentration 期刊论文  OAI收割 ATMOSPHERIC POLLUTION RESEARCH, 2018, 卷号: 9, 期号: 6, 页码: 989-999 作者:  Gan, Kai;  Sun, Shaolong;  Wang, Shouyang;  Wei, Yunjie   |  收藏  |  浏览/下载：55/0  |  提交时间：2018/11/16 Secondary-decomposition-ensemble learning paradigm  Complementary ensemble empirical mode decomposition  Phase space reconstruction  Least square support vector regression  Hybrid intelligent algorithm   A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting 期刊论文  OAI收割 APPLIED ENERGY, 2012, 卷号: 93, 期号: 1, 页码: 12,432-443 Tang, L; Yu, LA; Wang, S; Li, JP; Wang, SY 收藏  |  浏览/下载：36/0  |  提交时间：2012/11/12 Nuclear energy consumption forecasting  Hybrid ensemble learning paradigm  Ensemble empirical mode decomposition   Forecasting China's foreign trade volume with a kernel-based hybrid econometric-AI ensemble learning approach 期刊论文  OAI收割 JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2008, 卷号: 21, 期号: 1, 页码: 1-19 作者:  Yu, Lean;  Wang, Shouyang;  Lai, Kin Keung   |  收藏  |  浏览/下载：26/0  |  提交时间：2018/07/30 artificial neural networks  error-correction vector auto-regression  foreign trade prediction  hybrid ensemble learning  kernel-based method  support vector regression