Wind data modeling and forecasting | |
| Author | Sunida Chaokasem |
| Call Number | AIT Thesis no.IM-00-05 |
| Subject(s) | Wind forecasting Winds--Speed--Measurement |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. IM-00-05 |
| Abstract | In this study, hourly wind speed and direction at Promthep cape in Phuket, are forecasted and simulated using Box-Jenkins and Backpropagation approaches without the use of other external data. It was found that ARIMA models and seasonal ARIMA models are useful for short-range forecasting but are not very good in data generation. Backpropagation network models are good for forecasting and for generating data, which resemble the observed data in terms of the important statistics (mean, variance and skewness coefficient). For forecasting, Box-Jenkins models can perform slightly better than Backpropagation network models. However, for data generation (simulation), Backpropagation models can preserve the statistics of the observed data much better than Box-Jenkins models. |
| Year | 2000 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. IM-00-05 |
| Type | Thesis |
| School | School of Advanced Technologies (SAT) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information Management (IM) |
| Chairperson(s) | Phien, Huynh Ngoc; |
| Examination Committee(s) | Sadananda, Ramakoti;Tien, Hoang Le; |
| Scholarship Donor(s) | Royal Thai Government; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2000 |