A clonal selection algorithm model for daily rainfall data prediction

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 forecas...

Full description

Bibliographic Details
Main Authors:	Noor Rodi, Nur Syazwani, Abdul Malik, Marlinda, Sie Chun, Ting, Ismail , Amelia Ritahani, Tang, Chao-Wei
Format:	Article
Language:	English
Published:	IWA Publishing Journal 2014
Subjects:	QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General)
Online Access:	http://irep.iium.edu.my/39518/ http://irep.iium.edu.my/39518/ http://irep.iium.edu.my/39518/1/A_clonal_selection_algorithm_model_for_daily_rainfall_data-complete.pdf

id	iium-39518
recordtype	eprints
spelling	iium-395182015-04-01T10:41:27Z http://irep.iium.edu.my/39518/ A clonal selection algorithm model for daily rainfall data prediction Noor Rodi, Nur Syazwani Abdul Malik, Marlinda Sie Chun, Ting Ismail , Amelia Ritahani Tang, Chao-Wei QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) 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. IWA Publishing Journal 2014 Article PeerReviewed application/pdf en http://irep.iium.edu.my/39518/1/A_clonal_selection_algorithm_model_for_daily_rainfall_data-complete.pdf 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 http://www.iwaponline.com/wst/default.htm
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General)
spellingShingle	QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) Noor Rodi, Nur Syazwani Abdul Malik, Marlinda Sie Chun, Ting Ismail , Amelia Ritahani Tang, Chao-Wei A clonal selection algorithm model for daily rainfall data prediction
description	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.
format	Article
author	Noor Rodi, Nur Syazwani Abdul Malik, Marlinda Sie Chun, Ting Ismail , Amelia Ritahani Tang, Chao-Wei
author_facet	Noor Rodi, Nur Syazwani Abdul Malik, Marlinda Sie Chun, Ting Ismail , Amelia Ritahani Tang, Chao-Wei
author_sort	Noor Rodi, Nur Syazwani
title	A clonal selection algorithm model for daily rainfall data prediction
title_short	A clonal selection algorithm model for daily rainfall data prediction
title_full	A clonal selection algorithm model for daily rainfall data prediction
title_fullStr	A clonal selection algorithm model for daily rainfall data prediction
title_full_unstemmed	A clonal selection algorithm model for daily rainfall data prediction
title_sort	clonal selection algorithm model for daily rainfall data prediction
publisher	IWA Publishing Journal
publishDate	2014
url	http://irep.iium.edu.my/39518/ http://irep.iium.edu.my/39518/ http://irep.iium.edu.my/39518/1/A_clonal_selection_algorithm_model_for_daily_rainfall_data-complete.pdf
first_indexed	2023-09-18T20:56:47Z
last_indexed	2023-09-18T20:56:47Z
_version_	1777410357233451008

A clonal selection algorithm model for daily rainfall data prediction

Similar Items