中文版 | English

在结果中检索

CSpace

浏览/检索结果: 共6条，第1-6条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis 期刊论文
ENVIRONMENTAL MODELLING & SOFTWARE, 2022, 卷号: 149, 页码: 17
作者:  Li, Yanzhao;  Guo, Ju-e;  Sun, Shaolong;  Li, Jianing;  Wang, Shouyang;  Zhang, Chengyuan
收藏  |  浏览/下载：99/0  |  提交时间：2022/06/21
Air quality forecasting  Artificial intelligence  Machine learning  Scientometrics  Content analysis  
Forecasting hourly PM2.5 based on deep temporal convolutional neural network and decomposition method 期刊论文
APPLIED SOFT COMPUTING, 2021, 卷号: 113, 页码: 15
作者:  Jiang, Fuxin;  Zhang, Chengyuan;  Sun, Shaolong;  Sun, Jingyun
收藏  |  浏览/下载：117/0  |  提交时间：2022/04/29
PM2.5 concentration forecasting  Complete ensemble empirical mode  decomposition with adaptive noise  Temporal convolutional  Data patterns  Deep learning  
OPTIMAL MODEL AVERAGING BASED ON GENERALIZED METHOD OF MOMENTS 期刊论文
STATISTICA SINICA, 2021, 卷号: 31, 期号: 4, 页码: 2103-2122
作者:  Zhang, Xinyu
收藏  |  浏览/下载：126/0  |  提交时间：2022/04/02
Asymptotic optimality  consistency  generalized method of moments  model averaging  
Multimodel inference based on smoothed information criteria 期刊论文
SCIENCE CHINA-MATHEMATICS, 2021, 页码: 16
作者:  Zhao, Shangwei;  Zhang, Xinyu
收藏  |  浏览/下载：132/0  |  提交时间：2021/10/26
information criterion  model averaging  multimodel inference  variance estimation  weight  
A new decomposition ensemble approach for tourism demand forecasting: Evidence from major source countries in Asia-Pacific region 期刊论文
INTERNATIONAL JOURNAL OF TOURISM RESEARCH, 2021, 页码: 14
作者:  Zhang, Chengyuan;  Jiang, Fuxin;  Wang, Shouyang;  Sun, Shaolong
收藏  |  浏览/下载：171/0  |  提交时间：2021/04/26
artificial intelligence  Asia‐  Pacific region  decomposition ensemble approach  NA‐  MEMD  tourism demand forecasting  
A new ensemble deep learning approach for exchange rates forecasting and trading 期刊论文
ADVANCED ENGINEERING INFORMATICS, 2020, 卷号: 46, 页码: 10
作者:  Sun, Shaolong;  Wang, Shouyang;  Wei, Yunjie
收藏  |  浏览/下载：134/0  |  提交时间：2021/04/26
Ensemble learning  Forecasting  Trading  Deep learning  LSTM