Wind data modeling and forecasting
Call Number: AIT Thesis no.IM-00-05 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. IM-00-05Publication details: Bangkok : Asian Institute of Technology, 2000Description: 44 leavesSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology 2000 Summary: 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.
| Cover image | Item type | Current library | Home library | Collection | Shelving location | Call number | Materials specified | Vol info | URL | Copy number | Status | Notes | Date due | Barcode | Item holds | Item hold queue priority | Course reserves | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
22-AIT Thesis (Replacement)
|
Asian Institute of Technology Library AIT Publications | AIT Thesis no.IM-00-05 (Browse shelf(Opens below)) | 3 | Available | 30050120702054 | |||||||||||||
20-AIT Publication
|
Asian Institute of Technology Library AIT Publications | AIT Thesis no.IM-00-05 (Browse shelf(Opens below)) | 4 | Available | 30050120702047 | |||||||||||||
22-AIT Thesis (Replacement)
|
Asian Institute of Technology Library AIT Publications | AIT Thesis no.IM-00-05 (Browse shelf(Opens below)) | 5 | Available | 30050120702005 | |||||||||||||
40-Archives
|
Asian Institute of Technology Library Archives | AIT Thesis no.IM-00-05 (Browse shelf(Opens below)) | 1 | Available | 30050160073929 |
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies
Thesis (M.Eng.) - Asian Institute of Technology 2000
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.
There are no comments on this title.

AI Search