A hybrid forecasting approach applied to wind speed time series
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Summary
A hybrid forecasting approach, which combines the Ensemble Empirical Mode Decomposition (EEMD) and the Support Vector Machine (SVM), is proposed to improve the quality of wind speed forecasting to show great promise for the forecasting of intricate time series which are intrinsically highly volatile and irregular.
- Type
- article
- Published
- 2013-12-01
- Cited by
- 209
- References
- 30
- Access
- Open access
- OpenAlex
- https://openalex.org/W2011630059
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:109143497
Keywords
Hilbert–Huang transform, Wind speed, Residual, Mode (computer interface), Series (stratigraphy)
References
- Forecasting of the daily meteorological pollution using wavelets and support vector machine
- Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
- Application of a control algorithm for wind speed prediction and active power generation
- A comparison of various forecasting techniques applied to mean hourly wind speed time series
- Day-ahead wind speed forecasting using f-ARIMA models
- Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine
- Improvement of Auto-Regressive Integrated Moving Average models using Fuzzy logic and Artificial Neural Networks (ANNs)
- A locally recurrent fuzzy neural network with application to the wind speed prediction using spatial correlation
- Wind energy technology and current status : a review
- The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
- Analysis of wind power generation and prediction using ANN: A case study
- Locally recurrent neural networks for wind speed prediction using spatial correlation
- Rainfall forecasting by technological machine learning models
- De-noising option prices with the wavelet method
- Forecast of hourly average wind speed with ARMA models in Navarre (Spain)
- Modeling and forecasting the mean hourly wind speed time series using GMDH-based abductive networks
- Performance evaluation of object localization based on active radio frequency identification technology
- A neural networks approach for wind speed prediction
- Locally recurrent neural networks for long-term wind speed and power prediction
- Support vector machine-based models for hourly reservoir inflow forecasting during typhoon-warning periods
Cited by
- Short-term wind power prediction based on LSSVM–GSA model
- Diarrhoea outpatient visits prediction based on time series decomposition and multi-local predictor fusion
- Time Series Analysis and Forecasting for Wind Speeds Using Support Vector Regression Coupled with Artificial Intelligent Algorithms
- An Experimental Investigation of FNN Model for Wind Speed Forecasting Using EEMD and CS
- Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application
- Wind speed forecast correction models using polynomial neural networks
- Wind speed forecasting for wind farms: A method based on support vector regression
- A New Hybrid Model Based on an Intelligent Optimization Algorithm and a Data Denoising Method to Make Wind Speed Predication
- Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China
- Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model
- A hybrid technique for short-term wind speed prediction
- Hysteretic neural network and its application in the prediction of the wind speed series
- Lorenz Wind Disturbance Model Based on Grey Generated Components
- Improved wind prediction based on the Lorenz system
- Short-term prediction method of wind speed series based on fractal interpolation
- A Hybrid Approach for Short-Term Forecasting of Wind Speed
- A hybrid forecasting model based on outlier detection and fuzzy time series – A case study on Hainan wind farm of China
- Wind speed and direction prediction for wind farms using support vector regression
- Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)
- Empirical Mode Decomposition-k Nearest Neighbor Models for Wind Speed Forecasting
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