In this paper a time series prediction of wind speed with artificial neural networks is presented. For this purpose the mean hourly wind speed records for the area of Kourris dam, located at the south of Cyprus, are used. Wind data for ten consecutive years (1991-2000) are available for this area. The network was trained to predict the mean monthly hourly wind speed of a year (e.g. 1994) by using the values of wind speed for the same month, same hour for the three previous years (e.g. 1991-1993), consecutively. The data for the wind speed up to the year 1999 have been used for the training of the network whereas those for the years 1997-1999 (input) and 2000 (output) were used for the validation of the network. It should be noted tha...
Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess-ment,...
One of the most crucial prerequisites for effective wind power planning and operation in power syste...
An artificial neural network was used for forecasting of long-term wind speed data (24 and 48 hours ...
Abstract- Wind speed forecasting is an essential prerequisite for the planning, operation, and maint...
Wind speed-time series data typically exhibit autocorrelation, which can be defined as the degree o...
The aim of the present study is to apply an artificial neural network method for daily, weekly, and ...
In this study, artificial neural networks (ANNs) were applied to predict the mean monthly wind speed...
Predicting short term wind speed is essential in order to prevent systems in-action from the effects...
Abstract—Long-term forecasting of wind speed has become a research hot spot in many different areas ...
This paper presents a method for the medium-long-term wind speed prediction based on spatiotemporal ...
The growing concerns regarding the depletion of oil/gas reserves and global warming have made it ine...
Prediction is one of the most important techniques in determining the resulting wind speed. The deci...
One of the most crucial prerequisites for effective wind power planning and operation in power syste...
In this study, a new ANN estimation model has been developed in order to estimate wind speed in the ...
T. C. Akinci. Short Term Wind Speed Forecasting with ANN in Batman, Turkey // Electronics and Electr...
Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess-ment,...
One of the most crucial prerequisites for effective wind power planning and operation in power syste...
An artificial neural network was used for forecasting of long-term wind speed data (24 and 48 hours ...
Abstract- Wind speed forecasting is an essential prerequisite for the planning, operation, and maint...
Wind speed-time series data typically exhibit autocorrelation, which can be defined as the degree o...
The aim of the present study is to apply an artificial neural network method for daily, weekly, and ...
In this study, artificial neural networks (ANNs) were applied to predict the mean monthly wind speed...
Predicting short term wind speed is essential in order to prevent systems in-action from the effects...
Abstract—Long-term forecasting of wind speed has become a research hot spot in many different areas ...
This paper presents a method for the medium-long-term wind speed prediction based on spatiotemporal ...
The growing concerns regarding the depletion of oil/gas reserves and global warming have made it ine...
Prediction is one of the most important techniques in determining the resulting wind speed. The deci...
One of the most crucial prerequisites for effective wind power planning and operation in power syste...
In this study, a new ANN estimation model has been developed in order to estimate wind speed in the ...
T. C. Akinci. Short Term Wind Speed Forecasting with ANN in Batman, Turkey // Electronics and Electr...
Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess-ment,...
One of the most crucial prerequisites for effective wind power planning and operation in power syste...
An artificial neural network was used for forecasting of long-term wind speed data (24 and 48 hours ...