Wind Speed Prediction by Using Different Wavelet Conjunction Models
Three wavelet conjunction models, wavelet-genetic programming (WGEP), wavelet-neuro-fuzzy (WNF) and wavelet-neural network (WNN) were introduced in this paper for predicting hourly and daily wind speed values with three lag times. Hourly wind speed measurements from Darwin Airport synoptic station a...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2011-09-01
|
Series: | International Journal of Ocean and Climate Systems |
Online Access: | https://doi.org/10.1260/1759-3131.2.3.189 |
id |
doaj-c44ce180bcd44c569b08fa0433011dac |
---|---|
record_format |
Article |
spelling |
doaj-c44ce180bcd44c569b08fa0433011dac2020-11-25T01:54:57ZengSAGE PublishingInternational Journal of Ocean and Climate Systems1759-31311759-314X2011-09-01210.1260/1759-3131.2.3.18910.1260_1759-3131.2.3.189Wind Speed Prediction by Using Different Wavelet Conjunction ModelsOzgur Kisi0Jalal Shiri1Oleg Makarynskyy2 Engineering Faculty, Civil Engineering Department, Hydraulics Divisions, University of Erciyes, Kayseri, Turkey Water Engineering Department, Faculty of Agriculture, University of Tabriz, IR-51664 Tabriz, Iran URS Australia, 17/240 Queen St., Brisbane 4000, AustraliaThree wavelet conjunction models, wavelet-genetic programming (WGEP), wavelet-neuro-fuzzy (WNF) and wavelet-neural network (WNN) were introduced in this paper for predicting hourly and daily wind speed values with three lag times. Hourly wind speed measurements from Darwin Airport synoptic station and daily wind speed data from Tabriz Station (North-western Iran) were used as inputs to the wavelet conjunction models to predict 1-, 2- and 3-hour and 1-, 2- and 3-days ahead wind speeds. First, conventional GEP, NF and ANN models were applied to the wind speed time series. Then WGEP, WNF and WANN conjunction models were also used for the same purpose and their results were compared with those of the conventional GEP, NF and ANNs. The correlation coefficient, root mean squared error, scatter index and mean absolute error were used to evaluate the performance of the models. Inter-comparisons of model results indicated that the use of wavelet conjunction models increased the performance of the conventional GEP, ANFIS and ANN in forecasting hourly and daily wind speeds.https://doi.org/10.1260/1759-3131.2.3.189 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ozgur Kisi Jalal Shiri Oleg Makarynskyy |
spellingShingle |
Ozgur Kisi Jalal Shiri Oleg Makarynskyy Wind Speed Prediction by Using Different Wavelet Conjunction Models International Journal of Ocean and Climate Systems |
author_facet |
Ozgur Kisi Jalal Shiri Oleg Makarynskyy |
author_sort |
Ozgur Kisi |
title |
Wind Speed Prediction by Using Different Wavelet Conjunction Models |
title_short |
Wind Speed Prediction by Using Different Wavelet Conjunction Models |
title_full |
Wind Speed Prediction by Using Different Wavelet Conjunction Models |
title_fullStr |
Wind Speed Prediction by Using Different Wavelet Conjunction Models |
title_full_unstemmed |
Wind Speed Prediction by Using Different Wavelet Conjunction Models |
title_sort |
wind speed prediction by using different wavelet conjunction models |
publisher |
SAGE Publishing |
series |
International Journal of Ocean and Climate Systems |
issn |
1759-3131 1759-314X |
publishDate |
2011-09-01 |
description |
Three wavelet conjunction models, wavelet-genetic programming (WGEP), wavelet-neuro-fuzzy (WNF) and wavelet-neural network (WNN) were introduced in this paper for predicting hourly and daily wind speed values with three lag times. Hourly wind speed measurements from Darwin Airport synoptic station and daily wind speed data from Tabriz Station (North-western Iran) were used as inputs to the wavelet conjunction models to predict 1-, 2- and 3-hour and 1-, 2- and 3-days ahead wind speeds. First, conventional GEP, NF and ANN models were applied to the wind speed time series. Then WGEP, WNF and WANN conjunction models were also used for the same purpose and their results were compared with those of the conventional GEP, NF and ANNs. The correlation coefficient, root mean squared error, scatter index and mean absolute error were used to evaluate the performance of the models. Inter-comparisons of model results indicated that the use of wavelet conjunction models increased the performance of the conventional GEP, ANFIS and ANN in forecasting hourly and daily wind speeds. |
url |
https://doi.org/10.1260/1759-3131.2.3.189 |
work_keys_str_mv |
AT ozgurkisi windspeedpredictionbyusingdifferentwaveletconjunctionmodels AT jalalshiri windspeedpredictionbyusingdifferentwaveletconjunctionmodels AT olegmakarynskyy windspeedpredictionbyusingdifferentwaveletconjunctionmodels |
_version_ |
1724985930032349184 |