@inproceedings{oai:miyazaki-u.repo.nii.ac.jp:00002243,
 author = {Thungsuk, N. and Mungkung, Narong and Chaitanakulwat, A. and Yuji, T.},
 book = {1st Japan–Thailand Friendship International Workshop on Science Technology & Technology Education, Hand-making Education, Engineering Education, Environmental Education 2012},
 month = {},
 note = {This research, the Artificial Neural Networks (ANN) is proposed to estimate wind speed using wind turbine generator in comparison with data from the Thai Meteorological Department at Samut-Prakan station where is 1 km away. The results are studied to estimate the accuracy estimation of ANN. In experiment, data of wind speed from 150 W wind turbine generator are compared with data from Thai Meteorological Department at Samut-Prakan station where is 1 km away using MatLAB program. The stimulation of AN is investigated using input data from wind speed collected at the station from 2009 to 2010. The network of ANN use Tansig of transfer function for input and Purelin of transfer function for output. Input data was value between 0 - 1 from neural weights and bias value of ANN network will start from random value. There requirement of goal is zero and ANN has learning from wind speed record in year 2009 and year 2010 for 500 cycle. And has obtained 0.0573294 at Epochs, which that nearest of goal. The wind speed data average must error was 1.29 meter per second. The error of the lowest wind speed average was 0.03 m/s and the total average error is zero m/s. However the Neural network can be used to predict the wind speed from different location but there are some errors from unstable wind speed. However, the average of estimation is acceptable.},
 pages = {59--63},
 publisher = {Faculty of Education & Culture , University of Miyazaki},
 title = {Prediction of natural wind using neural networks for Wind turbine generator for install at Samut-Prakan, Thailand in year 2011},
 year = {2012}
}