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Short-term load forecasting with an improved dynamic decomposition-reconstruction-ensemble approach 期刊论文
ENERGY, 2023, 卷号: 263, 页码: 16
作者:  Yang, Dongchuan;  Guo, Ju-e;  Li, Yanzhao;  Sun, Shaolong;  Wang, Shouyang
收藏  |  浏览/下载：57/0  |  提交时间：2023/02/07
Short -term load forecasting  Time series modeling  Dynamic decomposition-reconstruction tech  nique  Neural networks  
A new PM2.5 concentration forecasting system based on AdaBoost-ensemble system with deep learning approach 期刊论文
JOURNAL OF FORECASTING, 2022, 页码: 22
作者:  Li, Zhongfei;  Gan, Kai;  Sun, Shaolong;  Wang, Shouyang
收藏  |  浏览/下载：68/0  |  提交时间：2023/02/07
AdaBoost-ensemble  deep learning  hybrid data preprocessing-analysis strategy  LSTM  
Daily tourism demand forecasting: the impact of complex seasonal patterns and holiday effects 期刊论文
CURRENT ISSUES IN TOURISM, 2022, 页码: 20
作者:  Liu, Yunhao;  Feng, Gengzhong;  Chin, Kwai-Sang;  Sun, Shaolong;  Wang, Shouyang
收藏  |  浏览/下载：171/0  |  提交时间：2022/06/21
Tourism demand forecasting  daily tourism demand  holiday effects  seasonal patterns  FB Prophet  
Regional variation in the drivers of China's residential electricity consumption (REC) and policy orientation 期刊论文
ENERGY FOR SUSTAINABLE DEVELOPMENT, 2022, 卷号: 67, 页码: 112-124
作者:  Wang, Shubin;  Sun, Shaolong;  Zhao, Erlong;  Wang, Shouyang
收藏  |  浏览/下载：102/0  |  提交时间：2022/06/21
Residential electricity consumption  Regional difference  LMDI method  China  
Forecasting daily tourism volume: a hybrid approach with CEMMDAN and multi-kernel adaptive ensemble 期刊论文
CURRENT ISSUES IN TOURISM, 2022, 页码: 20
作者:  Zhao, Erlong;  Du, Pei;  Azaglo, Ernest Young;  Wang, Shouyang;  Sun, Shaolong
收藏  |  浏览/下载：169/0  |  提交时间：2022/04/29
Daily tourism volume forecasting  decomposition ensemble approach  sample entropy  kernel extreme learning machine  multi-kernel adaptive strategy  
Seasonal and trend forecasting of tourist arrivals: An adaptive multiscale ensemble learning approach 期刊论文
INTERNATIONAL JOURNAL OF TOURISM RESEARCH, 2022, 页码: 18
作者:  Xing, Guangyuan;  Sun, Shaolong;  Bi, Dan;  Guo, Ju-e;  Wang, Shouyang
收藏  |  浏览/下载：122/0  |  提交时间：2022/04/02
ensemble learning  least square support vector regression  seasonality  tourism demand forecasting  variational mode decomposition  
An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting 期刊论文
APPLIED ENERGY, 2022, 卷号: 306, 页码: 16
作者:  Yang, Dongchuan;  Guo, Ju-E;  Sun, Shaolong;  Han, Jing;  Wang, Shouyang
收藏  |  浏览/下载：118/0  |  提交时间：2022/04/02
Short-term load forecasting  Bivariate empirical mode decomposition  Decomposition-ensemble approach  Reconstruction  Bayesian optimization  Long short-term memory network  
Volatility communicator or receiver? Investigating volatility spillover mechanisms among Bitcoin and other financial markets 期刊论文
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2022, 卷号: 59, 页码: 14
作者:  Jiang, Shangrong;  Li, Yuze;  Lu, Quanying;  Wang, Shouyang;  Wei, Yunjie
收藏  |  浏览/下载：128/0  |  提交时间：2022/04/02
Volatility spillover  Financial property  TVP-VAR model  Variational mode decomposition  Hypotheses testing  
A New Hybrid VMD-ICSS-BiGRU Approach for Gold Futures Price Forecasting and Algorithmic Trading 期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2021, 卷号: 8, 期号: 6, 页码: 1357-1368
作者:  Li, Yuze;  Wang, Shouyang;  Wei, Yunjie;  Zhu, Qing
收藏  |  浏览/下载：111/0  |  提交时间：2022/04/02
Gold  Forecasting  Autoregressive processes  Predictive models  Signal resolution  Deep learning  Mathematical model  Algorithmic trading  bidirectional gated recurrent unit (BiGRU)  gold futures price forecasting  variational mode decomposition (VMD)  
Air pollution forecasting with multivariate interval decomposition ensemble approach 期刊论文
ATMOSPHERIC POLLUTION RESEARCH, 2021, 卷号: 12, 期号: 12, 页码: 14
作者:  Dong, Yawei;  Zhang, Chengyuan;  Niu, Mingfei;  Wang, Shouyang;  Sun, Shaolong
收藏  |  浏览/下载：114/0  |  提交时间：2022/04/02
Daily PM 10 concentration forecast  Air quality  Interval forecasting  Noise-assisted multivariate empirical mode  decomposition  Maximum mutual information