Related references
Note: Only part of the references are listed.GHTnet: Tri-Branch deep learning network for real-time electricity price forecasting
Haolin Yang et al.
ENERGY (2022)
Real-time electricity price forecasting of wind farms with deep neural network transfer learning and hybrid datasets
Haolin Yang et al.
APPLIED ENERGY (2021)
An adaptive hybrid model for short term electricity price forecasting
Jinliang Zhang et al.
APPLIED ENERGY (2020)
Forecast the electricity price of US using a wavelet transform-based hybrid model
Weibiao Qiao et al.
ENERGY (2020)
Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm
Azim Heydari et al.
APPLIED ENERGY (2020)
Comparing the forecasting performances of linear models for electricity prices with high RES penetration
Angelica Gianfreda et al.
INTERNATIONAL JOURNAL OF FORECASTING (2020)
On the impact of outlier filtering on the electricity price forecasting accuracy
Dmitriy O. Afanasyev et al.
APPLIED ENERGY (2019)
Market price behavior of wholesale electricity products: Texas
J. Zarnikau et al.
ENERGY POLICY (2019)
Deep Long Short-Term Memory: A New Price and Load Forecasting Scheme for Big Data in Smart Cities
Sana Mujeeb et al.
SUSTAINABILITY (2019)
State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review
Ali Ehsan et al.
APPLIED ENERGY (2019)
ESAENARX and DE-RELM: Novel schemes for big data predictive analytics of electricity load and price
Sana Mujeeb et al.
SUSTAINABLE CITIES AND SOCIETY (2019)
Ensemble of relevance vector machines and boosted trees for electricity price forecasting
Rahul Kumar Agrawal et al.
APPLIED ENERGY (2019)
A review of deep learning for renewable energy forecasting
Huaizhi Wang et al.
ENERGY CONVERSION AND MANAGEMENT (2019)
Unsupervised Pre-training of a Deep LSTM-based Stacked Autoencoder for Multivariate Time Series Forecasting Problems
Alaa Sagheer et al.
SCIENTIFIC REPORTS (2019)
A Novel Electricity Price Forecasting Approach Based on Dimension Reduction Strategy and Rough Artificial Neural Networks
Hamidreza Jahangir et al.
IEEE Transactions on Industrial Informatics (2019)
Forecasting day-ahead electricity prices in Europe: The importance of considering market integration
Jesus Lago et al.
APPLIED ENERGY (2018)
Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms
Jesus Lago et al.
APPLIED ENERGY (2018)
A bat optimized neural network and wavelet transform approach for short-term price forecasting
P. M. R. Bento et al.
APPLIED ENERGY (2018)
Nonlinear empirical pricing in electricity markets using fundamental weather factors
Stephania Mosquera-Lopez et al.
ENERGY (2017)
Short-Term Electricity Price Forecasting With Stacked Denoising Autoencoders
Long Wang et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2017)
Deep and Confident Prediction for Time Series at Uber
Lingxue Zhu et al.
2017 17TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2017) (2017)
Visualising forecasting algorithm performance using time series instance spaces
Yanfei Kang et al.
INTERNATIONAL JOURNAL OF FORECASTING (2017)
Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by firefly algorithm
Deyun Wang et al.
APPLIED ENERGY (2017)
Electricity price forecasting by a hybrid model, combining wavelet transform, ARMA and kernel-based extreme learning machine methods
Zhang Yang et al.
APPLIED ENERGY (2017)
Day-ahead electricity price forecasting via the application of artificial neural network based models
Ioannis P. Panapakidis et al.
APPLIED ENERGY (2016)
A computationally efficient electricity price forecasting model for real time energy markets
Felipe Feijoo et al.
ENERGY CONVERSION AND MANAGEMENT (2016)
Deep learning in neural networks: An overview
Juergen Schmidhuber
NEURAL NETWORKS (2015)
Quantifying uncertainties of neural network-based electricity price forecasts
Abbas Khosravi et al.
APPLIED ENERGY (2013)
Convergence rates in l1-regularization if the sparsity assumption fails
Martin Burger et al.
INVERSE PROBLEMS (2013)
Load/Price Forecasting and Managing Demand Response for Smart Grids
S. C. Chan et al.
IEEE SIGNAL PROCESSING MAGAZINE (2012)
Electricity price forecasting using artificial neural networks
Deepak Singhal et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2011)
Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models
Zhongfu Tan et al.
APPLIED ENERGY (2010)
Analysis of the Nonlinear Response of Electricity Prices to Fundamental and Strategic Factors
Dipeng Chen et al.
IEEE TRANSACTIONS ON POWER SYSTEMS (2010)
Equilibrium pricing and optimal hedging in electricity forward markets
H Bessembinder et al.
JOURNAL OF FINANCE (2002)
Share Paper
