A hybrid model based on bidirectional long short-term memory neural network and Catboost for short-term electricity spot price forecasting
Author:
Affiliation:
1. Department of Microdata Analysis, Dalarna University, Falun, Sweden
2. Department of Energy Technology, Dalarna University, Falun, Sweden
3. Department of Computer Engineering, Dalarna University, Falun, Sweden
Publisher
Informa UK Limited
Subject
Marketing,Management Science and Operations Research,Strategy and Management,Management Information Systems
Link
https://www.tandfonline.com/doi/pdf/10.1080/01605682.2020.1843976
Reference54 articles.
1. A new prediction strategy for price spike forecasting of day-ahead electricity markets
2. Day-Ahead Deregulated Electricity Market Price Forecasting Using Recurrent Neural Network
3. Exploiting the past and the future in protein secondary structure prediction
4. Learning long-term dependencies with gradient descent is difficult
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