AI SearchForecasting the monthly discharge of the Mekong River
Call Number: AIT Thesis no. CA-83-25 Material type:
TextSeries: Asian Institute of Technology. Thesis ; no. CA-83-25Publication details: Bangkok : Asian Institute of Technology, 1983Description: viii, 86 pSubject(s): Online resources: Dissertation note: Thesis (M.Sc.) - Asian Institute of Technology, 1983 Summary: In this study, three different statistical methods are applied to forecast the monthly discharge of the MEKONG RIVER at five stations using only the discharge data. The Box-Jenkins model was used directly to forecast the monthly discharge using its own time series. Moreover, the Multiple Regression (MRG) and the Group Method of Data Handling (GMDH) are also employed to forecast the monthly discharge using additional information, such as the maximum and minimum daily values and the discharges of the last day in previous months. The results obtained show that all the three methods perform satisfactorily in providing forecasts with leas time equal to one month. The Box-Jenkins and Multiple Regression Analysis can be used to provide forecasts with long lead time, even though less accurate results are observed.
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22-AIT Thesis (Replacement)
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40-Archives
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Asian Institute of Technology Library Archives | AIT Thesis no. CA-83-25 (Browse shelf(Opens below)) | Available | 30050160064704 |
A thesis submitted in partial fulfillment of the requirement for the degree of Master of Science, School of Engineering and Technology
Thesis (M.Sc.) - Asian Institute of Technology, 1983
In this study, three different statistical methods are applied to forecast the monthly discharge of the MEKONG RIVER at five stations using only the discharge data. The Box-Jenkins model was used directly to forecast the monthly discharge using its own time series. Moreover, the Multiple Regression (MRG) and the Group Method of Data Handling (GMDH) are also employed to forecast the monthly discharge using additional information, such as the maximum and minimum daily values and the discharges of the last day in previous months. The results obtained show that all the three methods perform satisfactorily in providing forecasts with leas time equal to one month. The Box-Jenkins and Multiple Regression Analysis can be used to provide forecasts with long lead time, even though less accurate results are observed.
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