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Fuzzy case-based reasoning for weather prediction

Prediction is the process of the estimation of unknown situation that refers to time-series, cross sectional or longitudinal data. Weather prediction is the process to project how to atmosphere will evolve. Weather is known as continuous, data-intensive, multidimensional, dynamic and chaotic. The ch...

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Main Author: Wan Husain, Wan Salfarina
Format: Thesis
Language:English
Published: 2008
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/9524/1/WanSalfarinaMFSKSM2008.pdf
http://eprints.utm.my/id/eprint/9524/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:859?site_name=Restricted Repository
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spelling my.utm.95242018-07-19T01:51:14Z http://eprints.utm.my/id/eprint/9524/ Fuzzy case-based reasoning for weather prediction Wan Husain, Wan Salfarina QA75 Electronic computers. Computer science Prediction is the process of the estimation of unknown situation that refers to time-series, cross sectional or longitudinal data. Weather prediction is the process to project how to atmosphere will evolve. Weather is known as continuous, data-intensive, multidimensional, dynamic and chaotic. The chaotic nature of atmosphere required the massive computational power in order to solve the equations that describe the atmosphere, and the incomplete understanding of weather can make the prediction become less accurate. Based on this problem, Fuzzy Case-Based Reasoning (FCBR) is introduced in solving the prediction problem. Fuzzy can have the degree of truthfulness and falsehood that can handle uncertainty of the chaotic variables of the weather. Meanwhile Case Based Reasoning (CBR) has an ability to identify the similar cases from the past using the similarity measurement technique such as Euclidean distance. CBR can reduce the knowledge acquisition task and can reason with incomplete and imprecise data or knowledge. This study is conducted to investigate how fuzzy and CBR could solve the prediction problem and how it can improve its performance. From the experiment, it shows that the Fuzzy Case Based Reasoning has improved the accuracy of the weather prediction with achievement of 87%. 2008-10 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/9524/1/WanSalfarinaMFSKSM2008.pdf Wan Husain, Wan Salfarina (2008) Fuzzy case-based reasoning for weather prediction. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information System. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:859?site_name=Restricted Repository
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Wan Husain, Wan Salfarina
Fuzzy case-based reasoning for weather prediction
description Prediction is the process of the estimation of unknown situation that refers to time-series, cross sectional or longitudinal data. Weather prediction is the process to project how to atmosphere will evolve. Weather is known as continuous, data-intensive, multidimensional, dynamic and chaotic. The chaotic nature of atmosphere required the massive computational power in order to solve the equations that describe the atmosphere, and the incomplete understanding of weather can make the prediction become less accurate. Based on this problem, Fuzzy Case-Based Reasoning (FCBR) is introduced in solving the prediction problem. Fuzzy can have the degree of truthfulness and falsehood that can handle uncertainty of the chaotic variables of the weather. Meanwhile Case Based Reasoning (CBR) has an ability to identify the similar cases from the past using the similarity measurement technique such as Euclidean distance. CBR can reduce the knowledge acquisition task and can reason with incomplete and imprecise data or knowledge. This study is conducted to investigate how fuzzy and CBR could solve the prediction problem and how it can improve its performance. From the experiment, it shows that the Fuzzy Case Based Reasoning has improved the accuracy of the weather prediction with achievement of 87%.
format Thesis
author Wan Husain, Wan Salfarina
author_facet Wan Husain, Wan Salfarina
author_sort Wan Husain, Wan Salfarina
title Fuzzy case-based reasoning for weather prediction
title_short Fuzzy case-based reasoning for weather prediction
title_full Fuzzy case-based reasoning for weather prediction
title_fullStr Fuzzy case-based reasoning for weather prediction
title_full_unstemmed Fuzzy case-based reasoning for weather prediction
title_sort fuzzy case-based reasoning for weather prediction
publishDate 2008
url http://eprints.utm.my/id/eprint/9524/1/WanSalfarinaMFSKSM2008.pdf
http://eprints.utm.my/id/eprint/9524/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:859?site_name=Restricted Repository
_version_ 1643645177858883584
score 13.211869

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