Journal ArticleDOI
Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA–ANN model
Erasmo Cadenas,Wilfrido Rivera +1 more
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In this article, a hybrid model consisting of autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) was developed for wind speed forecasting in the Isla de Cedros in Baja California, in the Cerro de la Virgen in Zacatecas and in Holbox in Quintana Roo is presented.About:
This article is published in Renewable Energy.The article was published on 2010-12-01. It has received 358 citations till now. The article focuses on the topics: Autoregressive integrated moving average & Wind speed.read more
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Current status and future advances for wind speed and power forecasting
Jaesung Jung,Robert Broadwater +1 more
TL;DR: An overview of existing research on wind speed and power forecasting can be found in this article, where state-of-the-art approaches for wind power and wind speed forecasting are discussed.
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A review of combined approaches for prediction of short-term wind speed and power
TL;DR: In this article, a comprehensive research about the combined models is called on for how these models are constructed and affect the forecasting performance, and an up-to-date annotated bibliography of the wind forecasting literature is presented.
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Optimal parameters selection for BP neural network based on particle swarm optimization: A case study of wind speed forecasting
TL;DR: A Back Propagation neural network based on Particle Swam Optimization that combines PSO-BP with comprehensive parameter selection is introduced that achieves much better forecast performance than the basic back propagation neural network and ARIMA model.
Journal ArticleDOI
Short-term wind speed forecasting using wavelet transform and support vector machines optimized by genetic algorithm
TL;DR: A hybrid model combining with input selected by deep quantitative analysis, Wavelet Transform, Genetic Algorithm,GA and Support Vector Machines (SVM) was proposed, which outperforms the comparison models in predicting wind speed.
Journal ArticleDOI
A moving-average filter based hybrid ARIMA-ANN model for forecasting time series data
C. Narendra Babu,B. Eswara Reddy +1 more
TL;DR: The linear autoregressive integrated moving average (ARIMA) and nonlinear artificial neural network (ANN) models are explored in this paper to devise a new hybrid ARIMA-ANN model for the prediction of time series data.
References
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Book
Forecasting: Methods and Applications
TL;DR: The authors presents a wide range of forecasting methods useful for undergraduate or graduate students majoring in business management, economics, or engineering, including decomposition, regression analysis, and econometrics.
Journal ArticleDOI
A review on the forecasting of wind speed and generated power
TL;DR: A bibliographical survey on the general background of research and developments in the fields of wind speed and wind power forecasting and further direction for additional research and application is proposed.
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Artificial neural networks in renewable energy systems applications: a review
TL;DR: In this article, the authors present various applications of neural networks mainly in renewable energy problems in a thematic rather than a chronological or any other order, which clearly suggest that artificial neural networks can be used for modelling in other fields of renewable energy production and use.
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Day-ahead wind speed forecasting using f-ARIMA models
TL;DR: In this article, the authors examined the use of fractional-ARIMA or f-ARAMA models to model, and forecast wind speeds on the day-ahead and two-day-ahead (48 h) horizons.
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Forecast of hourly average wind speed with ARMA models in Navarre (Spain)
TL;DR: It has been proven that the transformation and standardization of the original series allow the use of ARMA models and these behave significantly better in the forecast than the persistence model, especially in the longer-term forecasts.