A hybrid model for multi-step coal price forecasting using decomposition technique and deep learning algorithms
发布时间：2022-01-15点击次数：
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影响因子：9.746
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DOI码：10.1016/j.apenergy.2021.118011
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发表刊物：Applied Energy
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关键字：Coal price forecasting; Variational mode decomposition (VMD); Attention mechanism; LSTMSVR
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摘要：Accurate and reliable coal price prediction is of great significance to enhance the stability of the coal market. Numerous methods have been developed to improve the prediction performance. However, most of the studies adopt single model for coal price forecasting, and their accuracy and applicability are usually restricted. In this paper, we propose a novel hybrid VMD-A-LSTM-SVR model to achieve accurate multi-step ahead prediction of coal price. The proposed model consists of three valuable strategies. First, variational mode decomposition (VMD) decomposes the original coal price into several relatively regular sub modes to reduce the non-stationarity and uncertainty of the data. Second, the long short-term memory (LSTM) integrated with attention mechanism trains and predicts the decomposed modes individually to better capture the temporal information of historical data. Lastly, a support vector regression (SVR) model ensembles the predicted results of each mode into the final forecasted coal price. The experimental results of three typical coal price datasets demonstrate that the proposed strategies are all valuable for improving the forecasting performance. Moreover, the proposed model outperforms all state-of-the-art baseline models in terms of both model accuracy and stability. Extensive cross-comparisons of performance between models clearly indicate that the proposed hybrid algorithm is more effective and practical for coal price forecasting.
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论文类型：期刊论文
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卷号：306
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页面范围：118011
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是否译文：否
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收录刊物：SCI
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俞和胜
职务：Professor
主要任职：
个人信息
- 教授
博士生导师
硕士生导师 - 教师拼音名称：yuhesheng
- 电子邮箱：
- 所在单位：化工学院
- 职务：Professor
- 办公地点：中国矿业大学文昌校区综合楼203
- 性别：男
- 学位：博士
- 职称：教授
- 毕业院校：加拿大滑铁卢大学
学术荣誉：
- 2020当选：江苏特聘教授
曾获荣誉：
- 2020-08-01江苏特聘教授
- 2014-10-15加拿大国家自然科学基金工业博士后奖学金
- 2020-08-01中国矿业大学“高端人才计划”攀登学者
- 2019-06-01江苏省“六大人才高峰”高层次人才
- 2018-06-28江苏省“双创博士”
- 2016-08-01AIChE Journal Editor’s Choice Paper
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