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Sains Malaysiana 46(12)(2017): 2541–2547 http://dx.doi.org/10.17576/jsm-2017-4612-32
A Hybrid Climate Model for Rainfall
Forecasting based on Combination of Self-Organizing Map and
Analog Method (Model Iklim
Hibrid untuk Ramalan
Curahan Hujan
berdasarkan Gabungan Peta Swaurus dan Kaedah
Analog) NATITA WANGSOH1,
WIBOONSAK
WATTHAYU1*
& DUSADEE SUKAWAT2 1Department of Mathematics, Faculty
of Science, King Mongkut’s University of Technology, Thonburi
(KMUTT), 126 Pracha Uthit
Rd., Bang Mod, Thung Khru,
Bangkok 10140, Thailand 2Joint Graduate School of Energy
and Environment, KMUTT, 126 Pracha
Uthit Rd., Bang Mod, Thung Khru, Bangkok 10140, Thailand Received: 22 November 2016/Accepted:
1 April 2017 ABSTRACT A hybrid climate model (HCM)
is a novel proposed model based on the combination of self-organizing
map (SOM)
and analog method (AM). The main purpose was to improve
the accuracy in rainfall forecasting using HCM.
In combination process of HCM, SOM algorithm
classifies high dimensional input data to low dimensional of
several disjointed clusters in which similar input is grouped.
AM searches the future day that has
similar property with the day in the past. Consequently, the
analog day is mapped to each cluster of SOM to
investigate rainfall. In this study, the input data, geopotential
height at 850 hPa from the Climate
Forecast System Reanalysis (CFSR)
are training set data and also the complete rainfall data at
30-meteorological stations from Thai meteorological department
(TMD)
are observed. To improve capability of rainfall forecasting,
three different measures were evaluated. The experimental results
showed that the performance of HCM is better than the traditional AM.
It is illustrated that the HCM can forecast rainfall proficiently.
Keywords: Analog method; hybrid
climate model; rainfall forecasting; self-organizing map ABSTRAK Model iklim
hibrid (HCM) adalah
model cadangan novel berdasarkan
peta swaurus
(SOM)
dan kaedah
analog (AM).
Tujuan
utama kajian ialah
untuk meningkatkan
ketepatan dalam peramalan curahan hujan menggunakan HCM.
Dalam proses gabungan
HCM,
algoritma SOM mengelaskan
data input dimensi yang tinggi
kepada dimensi
rendah daripada beberapa kelompok terputus dengan input yang sama dikumpulkan.
AM
mencari hari akan datang yang mempunyai sifat yang sama dengan hari pada masa lalu. Oleh yang demikian, hari analog dipetakan
kepada setiap kluster
SOM
untuk mengkaji
curahan hujan.
Dalam kajian ini,
input data, ketinggian geopotensi
pada 850 hPa
daripada Sistem Iklim Ramalan Analisis
Semula (CFSR) adalah
data set latihan dan
juga data lengkap curahan
hujan di 30 stesen meteorologi daripada Jabatan Meteorologi Thailand (TMD)
adalah curahan
hujan yang dicerap. Untuk memperbaiki keupayaan ramalan curahan hujan, tiga langkah
berbeza telah
dinilai. Keputusan uji kaji menunjukkan prestasi HCM
adalah lebih baik
daripada AM tradisi.
Ditunjukkan bahawa HCM boleh meramalkan hujan dengan cekap.
Kata kunci: Kaedah
analog; model hibrid iklim
hujan ramalan; peta swaurus REFERENCES Allan, H. 2009. A Concise Guide to Clinical Trials. Oxford: John Wiley
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