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Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks 期刊论文
ENERGY, 2022, 卷号: 238, 页码: 22
Authors:  Li, Dan;  Jiang, Fuxin;  Chen, Min;  Qian, Tao
Favorite  |  View/Download:59/0  |  Submit date:2022/04/02
Wind speed forecasting  Ensemble patch transform  Complete ensemble empirical mode  decomposition  Temporal convolutional network  Hybrid method  
A novel multiscale forecasting model for crude oil price time series 期刊论文
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2021, 卷号: 173, 页码: 15
Authors:  Li, Ranran;  Hu, Yucai;  Heng, Jiani;  Chen, Xueli
Favorite  |  View/Download:43/0  |  Submit date:2022/04/02
Crude oil price forecasting  Decomposition-ensemble method  Support vector machine  Multiscale strategy  Complexity 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
Authors:  Jiang, Fuxin;  Zhang, Chengyuan;  Sun, Shaolong;  Sun, Jingyun
Favorite  |  View/Download:39/0  |  Submit date:2022/04/29
PM2.5 concentration forecasting  Complete ensemble empirical mode  decomposition with adaptive noise  Temporal convolutional  Data patterns  Deep learning  
Decomposition Methods for Tourism Demand Forecasting: A Comparative Study 期刊论文
JOURNAL OF TRAVEL RESEARCH, 2021, 页码: 18
Authors:  Zhang, Chengyuan;  Li, Mingchen;  Sun, Shaolong;  Tang, Ling;  Wang, Shouyang
Favorite  |  View/Download:43/0  |  Submit date:2022/04/02
tourism demand forecasting  decomposition methods  variational mode decomposition  decomposition and ensemble  machine learning  
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
Authors:  Zhang, Chengyuan;  Jiang, Fuxin;  Wang, Shouyang;  Sun, Shaolong
Favorite  |  View/Download:69/0  |  Submit date:2021/04/26
artificial intelligence  Asia‐  Pacific region  decomposition ensemble approach  NA‐  MEMD  tourism demand forecasting  
Interval forecasting of exchange rates: a new interval decomposition ensemble approach 期刊论文
INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2020, 页码: 28
Authors:  Sun, Shaolong;  Wang, Shouyang;  Wei, Yunjie
Favorite  |  View/Download:78/0  |  Submit date:2020/05/24
Exchange rate forecasting  Interval-valued data  Autoregressive model  Neural networks  Bivariate empirical mode decomposition  
A multi-scale method for forecasting oil price with multi-factor search engine data 期刊论文
APPLIED ENERGY, 2020, 卷号: 257, 页码: 12
Authors:  Tang, Ling;  Zhang, Chengyuan;  Li, Ling;  Wang, Shouyang
Favorite  |  View/Download:83/0  |  Submit date:2020/05/24
Big data  Search engine data  Google trends  Multivariate empirical mode decomposition  Oil price forecasting  
A new multiscale decomposition ensemble approach for forecasting exchange rates 期刊论文
ECONOMIC MODELLING, 2019, 卷号: 81, 页码: 49-58
Authors:  Sun, Shaolong;  Wang, Shouyang;  Wei, Yunjie
Favorite  |  View/Download:97/0  |  Submit date:2020/01/10
Exchange rates forecasting  Variational mode decomposition  Support vector regression  Support vector neural network  Ensemble learning  
A secondary-decomposition-ensemble learning paradigm for forecasting PM2.5 concentration 期刊论文
ATMOSPHERIC POLLUTION RESEARCH, 2018, 卷号: 9, 期号: 6, 页码: 989-999
Authors:  Gan, Kai;  Sun, Shaolong;  Wang, Shouyang;  Wei, Yunjie
Favorite  |  View/Download:146/0  |  Submit date:2018/11/16
Secondary-decomposition-ensemble learning paradigm  Complementary ensemble empirical mode decomposition  Phase space reconstruction  Least square support vector regression  Hybrid intelligent algorithm  
Interval decomposition ensemble approach for crude oil price forecasting 期刊论文
ENERGY ECONOMICS, 2018, 卷号: 76, 页码: 274-287
Authors:  Sun, Shaolong;  Sun, Yuying;  Wang, Shouyang;  Wei, Yunjie
Favorite  |  View/Download:105/0  |  Submit date:2019/03/05
Bivariate empirical mode decomposition  Crude oil price forecasting  Interval-valued time series  Interval Holt's method  Interval neural networks