A Novel Hybrid Strategy Using Three-Phase Feature Extraction and a Weighted Regularized Extreme Learning Machine for Multi-Step Ahead Wind Speed Prediction
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Novel Hybrid Strategy Using Three-Phase Feature Extraction and a Weighted Regularized Extreme Learning Machine for Multi-Step Ahead Wind Speed Prediction
Authors
Keywords
-
Journal
Energies
Volume 11, Issue 2, Pages 321
Publisher
MDPI AG
Online
2018-02-02
DOI
10.3390/en11020321
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A Least Squares Support Vector Machine Optimized by Cloud-Based Evolutionary Algorithm for Wind Power Generation Prediction
- (2016) Qunli Wu et al. Energies
- A new wind power prediction method based on chaotic theory and Bernstein Neural Network
- (2016) Cong Wang et al. ENERGY
- A new intelligent method based on combination of VMD and ELM for short term wind power forecasting
- (2016) Ali Akbar Abdoos NEUROCOMPUTING
- Comparison of new hybrid FEEMD-MLP, FEEMD-ANFIS, Wavelet Packet-MLP and Wavelet Packet-ANFIS for wind speed predictions
- (2015) Hui Liu et al. ENERGY CONVERSION AND MANAGEMENT
- Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms
- (2015) Hui Liu et al. ENERGY CONVERSION AND MANAGEMENT
- Error analysis of hybrid photovoltaic power forecasting models: A case study of mediterranean climate
- (2015) Maria Grazia De Giorgi et al. ENERGY CONVERSION AND MANAGEMENT
- Outlier-robust extreme learning machine for regression problems
- (2015) Kai Zhang et al. NEUROCOMPUTING
- A self-adaptive hybrid approach for wind speed forecasting
- (2015) Jianzhou Wang et al. RENEWABLE ENERGY
- Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China
- (2015) Jianzhou Wang et al. RENEWABLE ENERGY
- A Comparative Study of Empirical Mode Decomposition-Based Short-Term Wind Speed Forecasting Methods
- (2015) Ye Ren et al. IEEE Transactions on Sustainable Energy
- Support vector regression methodology for wind turbine reaction torque prediction with power-split hydrostatic continuous variable transmission
- (2014) Shahaboddin Shamshirband et al. ENERGY
- Wind speed estimation using multilayer perceptron
- (2014) Ramón Velo et al. ENERGY CONVERSION AND MANAGEMENT
- Variational Mode Decomposition
- (2014) Konstantin Dragomiretskiy et al. IEEE TRANSACTIONS ON SIGNAL PROCESSING
- On the computational complexity of the empirical mode decomposition algorithm
- (2014) Yung-Hung Wang et al. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
- Current status and future advances for wind speed and power forecasting
- (2014) Jaesung Jung et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Pattern-Based Wind Speed Prediction Based on Generalized Principal Component Analysis
- (2014) Qinghua Hu et al. IEEE Transactions on Sustainable Energy
- A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction
- (2013) Jie Yu et al. ENERGY
- Multifractal description of wind power fluctuations using arbitrary order Hilbert spectral analysis
- (2013) Rudy Calif et al. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
- Wind speed and wind energy forecast through Kalman filtering of Numerical Weather Prediction model output
- (2012) Federico Cassola et al. APPLIED ENERGY
- Modeling of atmospheric wind speed sequence using a lognormal continuous stochastic equation
- (2012) R. Calif et al. JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
- Evaluation of hybrid forecasting approaches for wind speed and power generation time series
- (2012) Jing Shi et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks
- (2012) Hui Liu et al. RENEWABLE ENERGY
- A corrected hybrid approach for wind speed prediction in Hexi Corridor of China
- (2011) Zhenhai Guo et al. ENERGY
- Fine tuning support vector machines for short-term wind speed forecasting
- (2011) Junyi Zhou et al. ENERGY CONVERSION AND MANAGEMENT
- Extreme Learning Machine for Regression and Multiclass Classification
- (2011) Guang-Bin Huang et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
- A case study on a hybrid wind speed forecasting method using BP neural network
- (2011) Zhen-hai Guo et al. KNOWLEDGE-BASED SYSTEMS
- Regularized extreme learning machine for regression problems
- (2011) José M. Martínez-Martínez et al. NEUROCOMPUTING
- Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
- (2011) Zhenhai Guo et al. RENEWABLE ENERGY
- On comparing three artificial neural networks for wind speed forecasting
- (2010) Gong Li et al. APPLIED ENERGY
- ARMA based approaches for forecasting the tuple of wind speed and direction
- (2010) Ergin Erdem et al. APPLIED ENERGY
- Prediction of wind speed time series using modified Taylor Kriging method
- (2010) Heping Liu et al. ENERGY
- Stochastic models for wind speed forecasting
- (2010) S. Bivona et al. ENERGY CONVERSION AND MANAGEMENT
- Very short-term wind speed prediction: A new artificial neural network–Markov chain model
- (2010) S.A. Pourmousavi Kani et al. ENERGY CONVERSION AND MANAGEMENT
- Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering
- (2008) P. Louka et al. JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
- Improvement of Auto-Regressive Integrated Moving Average models using Fuzzy logic and Artificial Neural Networks (ANNs)
- (2008) Mehdi Khashei et al. NEUROCOMPUTING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started