Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test
The reliability of extreme estimates of hydro-meteorological events such as extreme rainfalls may be questionable due to limited historical rainfall records. The problem of limited rainfall records, however, can be overcome by extrapolating information from gauged to ungauged rainfall catchments, wh...
Main Authors: | Chuan, Zun Liang, Noriszura, Ismail, Wan Nur Syahidah, Wan Yusoff, Soo-Fen, Fam, Mohd Akramin, Mohd Romlay |
---|---|
Format: | Article |
Language: | English |
Published: |
Science Publishing Corporation
2018
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/22702/ http://umpir.ump.edu.my/id/eprint/22702/ http://umpir.ump.edu.my/id/eprint/22702/1/Identifying%20homogeneous%20rainfall%20catchments%20for%20non-%20stationary%20time%20series%20using%20tops%20is%20algorithm%20and%20bootstrap%20k-sample%20Anderson%20darling%20test.pdf |
Similar Items
-
The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
by: Chuan, Zun Liang, et al.
Published: (2018) -
Modelling and Simulation of Volumetric Rainfall for a Catchment in the Murray-Darling Basin
by: Boland, J. W., et al.
Published: (2016) -
Topsy-Turvy
by: Ruditis
Published: (2002) -
Statistical distribution for prediction of stress intensity factor using bootstrap s-version finite element model
by: M. N., M. Husnain, et al.
Published: (2019) -
Markov chain model and stationary test: a case study on
Malaysia Social Security (SOCSO)
by: Shamshimah Samsuddin,, et al.
Published: (2019)