Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling
出版年份 2021 全文链接
标题
Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling
作者
关键词
Deep learning, Electricity price forecasting (EPF), Electricity market coupling, Feature selection, Long short-term memory (LSTM), The Nord Pool system price
出版物
ENERGY
Volume 237, Issue -, Pages 121543
出版商
Elsevier BV
发表日期
2021-07-27
DOI
10.1016/j.energy.2021.121543
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Prediction of photovoltaic power output based on similar day analysis, genetic algorithm and extreme learning machine
- (2020) Yi Zhou et al. ENERGY
- Characterizing electricity market integration in Nord Pool
- (2020) Jorge M. Uribe et al. ENERGY
- A novel GA-ELM model for patient-specific mortality prediction over large-scale lab event data
- (2019) Gokul S. Krishnan et al. APPLIED SOFT COMPUTING
- Electricity Price Prediction Based on Hybrid Model of Adam optimized LSTM Neural Network and Wavelet Transform
- (2019) Zihan Chang et al. ENERGY
- Development of soft sensors for isomerization process based on support vector machine regression and dynamic polynomial models
- (2019) Srečko Herceg et al. CHEMICAL ENGINEERING RESEARCH & DESIGN
- Predicting residential energy consumption using CNN-LSTM neural networks
- (2019) Tae-Young Kim et al. ENERGY
- Forecasting day-ahead electricity prices in Europe: The importance of considering market integration
- (2018) Jesus Lago et al. APPLIED ENERGY
- Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms
- (2018) Jesus Lago et al. APPLIED ENERGY
- Forecasting Functional Time Series with a New Hilbertian ARMAX Model: Application to Electricity Price Forecasting
- (2018) Jose Portela Gonzalez et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Recent advances in electricity price forecasting: A review of probabilistic forecasting
- (2018) Jakub Nowotarski et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- An Electricity Price Forecasting Model by Hybrid Structured Deep Neural Networks
- (2018) Ping-Huan Kuo et al. Sustainability
- Maximization of energy absorption for a wave energy converter using the deep machine learning
- (2018) Liang Li et al. ENERGY
- SVM-RFE: selection and visualization of the most relevant features through non-linear kernels
- (2018) Hector Sanz et al. BMC BIOINFORMATICS
- A new electricity price prediction strategy using mutual information-based SVM-RFE classification
- (2017) Zhen Shao et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks
- (2016) Dogan Keles et al. APPLIED ENERGY
- Day-ahead electricity price forecasting via the application of artificial neural network based models
- (2016) Ioannis P. Panapakidis et al. APPLIED ENERGY
- Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting
- (2016) Bartosz Uniejewski et al. Energies
- Sequential wavelet-ANN with embedded ANN-PSO hybrid electricity price forecasting model for Indian energy exchange
- (2016) Smitha Elsa Peter et al. NEURAL COMPUTING & APPLICATIONS
- New mechanism for archive maintenance in PSO-based multi-objective feature selection
- (2016) Hoai Bach Nguyen et al. SOFT COMPUTING
- Particle swarm optimization-based feature selection in sentiment classification
- (2016) Lin Shang et al. SOFT COMPUTING
- An integrated PSO for parameter determination and feature selection of ELM and its application in classification of power system disturbances
- (2015) R. Ahila et al. APPLIED SOFT COMPUTING
- Electricity futures price models: Calibration and forecasting
- (2015) Suren Islyaev et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- The ACEWEM framework: An integrated agent-based and statistical modelling laboratory for repeated power auctions
- (2015) Daniil Kiose et al. EXPERT SYSTEMS WITH APPLICATIONS
- A survey on feature selection methods
- (2013) Girish Chandrashekar et al. COMPUTERS & ELECTRICAL ENGINEERING
- Evolutionary ELM wrapper feature selection for Alzheimer's disease CAD on anatomical brain MRI
- (2013) Darya Chyzhyk et al. NEUROCOMPUTING
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
- ICGA-PSO-ELM Approach for Accurate Multiclass Cancer Classification Resulting in Reduced Gene Sets in Which Genes Encoding Secreted Proteins Are Highly Represented
- (2010) S Saraswathi et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- Economic Impact of Electricity Market Price Forecasting Errors: A Demand-Side Analysis
- (2009) H. Zareipour et al. IEEE TRANSACTIONS ON POWER SYSTEMS
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started