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035 _a.b10290631
099 9 _aAIT Thesis no. CA-83-25
100 1 _aTwu, Chung-tung
245 1 0 _aForecasting the monthly discharge of the Mekong River
260 _aBangkok :
_bAsian Institute of Technology,
_c1983
300 _aviii, 86 p.
490 1 _aThesis ;
_vno. CA-83-25
500 _aA thesis submitted in partial fulfillment of the requirement for the degree of Master of Science, School of Engineering and Technology
502 _aThesis (M.Sc.) - Asian Institute of Technology, 1983
520 _aIn 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.
650 0 _aStream measurements
_xMekong River
700 1 _aHuynh, Ngoc Phien,
_eChairperson
700 0 _aKanchit Malaivongs,
_eExamination Committee
700 1 _aLe Huu Ti,
_eExamination Committee
710 2 _aThe Government of Germany, Carl Duisberg-Gesellschaft e. V. (CDG),
_eScholarship Donor
810 2 _aAsian Institute of Technology.
_tThesis ;
_vno. CA-83-25
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B20964
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