A clonal selection algorithm model for daily rainfall data prediction

Noor Rodi, Nur Syazwani and Abdul Malik, Marlinda and Sie Chun, Ting and Ismail , Amelia Ritahani and Tang, Chao-Wei (2014) A clonal selection algorithm model for daily rainfall data prediction. Water Science and Technology , 70 (10). pp. 1641-1647. ISSN 0273-1223

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Abstract

This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. The stochastic and the artificial neural network techniques are commonly used in hydrology. However, in this study a novel technique for forecasting rainfall was established. Results from this study have proven that the theory of biological immune systems could be technically applied to time series data. Biological immune systems are nonlinear and chaotic in nature similar to the daily rainfall data. This study discovered that the proposed CSA was able to predict the daily rainfall data with an accuracy of 90% during the model training stage. In the testing stage, the results showed that an accuracy between the actual and the generated data was within the range of 75 to 92%. Thus, the CSA approach shows a new method in rainfall data prediction.

Item Type:	Article (Journal)
Additional Information:	4296/39518
Uncontrolled Keywords:	artificial immune system, clonal selection algorithm, daily rainfall, prediction
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TA Engineering (General). Civil engineering (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Amelia Ritahani Ismail
Date Deposited:	05 Dec 2014 16:24
Last Modified:	01 Apr 2015 18:41
URI:	http://irep.iium.edu.my/id/eprint/39518

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