Evaluation of regression methods in flow forecasting (Record no. 41168)

MARC details
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005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260818112807.0
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035 ## - SYSTEM CONTROL NUMBER
System control number .b10261230
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Bui Khanh Huong
245 10 - TITLE STATEMENT
Title Evaluation of regression methods in flow forecasting
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Bangkok :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 1988
300 ## - PHYSICAL DESCRIPTION
Extent 66 p.
490 1# - SERIES STATEMENT
Series statement Thesis ;
Volume/sequential designation no. CS-88-4
500 ## - GENERAL NOTE
General note A thesis submitted in partial fulfillment of the requirement for the degree of Master of Science, School of Engineering and Technology
502 ## - DISSERTATION NOTE
Dissertation note Thesis (M.Sc.) - Asian Institute of Technology, 1988
520 ## - SUMMARY, ETC.
Summary, etc. In this thesis a system is developed for daily flow forecasting consisting o f five regression methods: - The Least Squares Method, - The Ridge Regression , - The Principal Component Regression, - The Stepwise Regression, a nd - The regression with minimum s um of absolute errors. The system was used to evaluate the performances of the regression techniques and of the following models: - The - The - The - The model involving discharge, rainfall and evaporation, mode l using only discharge and rainfall, Linear Perturbation Mode l, a nd Extended Linear Perturbation Model. From applications to data on two catchment areas , in Laos and Th ail and , it was found that: - The performances of the least squares method, the stepwise regression and the regression with minimum sum of absolute errors are almost the same. But the regression with mini mum sum of absolute errors requires mu c h more executing time. - The performance of the ridge regression is not as good as that of the least squares method in the case of nonsingular matrix . The ridge regression is recommended for use only when the least squares method cannot give the results because of the multicollinearity present among the predictor variables. - The performance of the principal component regression is a l so not as good as that of the least squares method. - The performances of the model involving discharge, rainfall and evaporation , the model using only discharge and rain fall, and the Extended Linear Perturbation Model are almost t he same. - The performance of the model using only discharge and rainfall is better than that of the Linear Perturbation Model.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Hydraulics
General subdivision Mathematical models
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Huynh, Ngoc Phien,
Relator term Chairperson
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Bogardi, Janos J.,
Relator term Examination Committee
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Gonzales, Jr. R. L.,
Relator term Examination Committee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Japanese Government,
Relator term Scholarship Donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Thesis ;
Volume/sequential designation no. CS-88-4
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href="http://203.159.5.9/ait-thesis/detail.php?q=B18762">http://203.159.5.9/ait-thesis/detail.php?q=B18762</a>
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998 ## - LOCAL CONTROL INFORMATION (RLIN)
Operator's initials, OID (RLIN) 2
Cataloger's initials, CIN (RLIN) 951012
First date, FD (RLIN) m
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 20-AIT Publication
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 40-Archives
909 ## - LOCAL ITEMS USED
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CREATED CREATED : 1994-05-17
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      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library AIT Publications 18/08/2026   30050003148334 18/08/2026 2 18/08/2026 20-AIT Publication
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