Agent oriented methodology for malaria transmission modelling and simulation
Epidemiology study like malaria study is receiving much attention among the researchers nowadays. To model the epidemiology study like malaria, one can adopt different equations to formulate the problem.Alternatively, individual based modelling is started to emerge and useful for epidemiology study...
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my.uum.repo.228192017-07-26T08:16:59Z http://repo.uum.edu.my/22819/ Agent oriented methodology for malaria transmission modelling and simulation Loh, Chee Wyai Nissom, Shane Cheah, Wai Shiang Jali, Nurfauza QA75 Electronic computers. Computer science Epidemiology study like malaria study is receiving much attention among the researchers nowadays. To model the epidemiology study like malaria, one can adopt different equations to formulate the problem.Alternatively, individual based modelling is started to emerge and useful for epidemiology study due to the nature of flexibility ad emergence behaviour of individual based modelling. Since various epidemiology mathematical models has been introduced and implemented, can we reuse the models in individual based modelling? In fact, it is possible but not a straightforward process. This paper presents a systematical approach for individual based epidemiology modelling and simulation by reusing the existing mathematical models on epidemiology study.With the systematic approach, a rapidly prototyping of epidemiology study is introduced.Also, it promotes the comprehensiveness and model transformation across technical and non-technical person. 2017-04-25 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/22819/1/ICOCI%202017%20160-166.pdf Loh, Chee Wyai and Nissom, Shane and Cheah, Wai Shiang and Jali, Nurfauza (2017) Agent oriented methodology for malaria transmission modelling and simulation. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur. http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap03e/PID51-160-166e.pdf |
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QA75 Electronic computers. Computer science Loh, Chee Wyai Nissom, Shane Cheah, Wai Shiang Jali, Nurfauza Agent oriented methodology for malaria transmission modelling and simulation |
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Epidemiology study like malaria study is receiving much attention among the researchers nowadays. To model the epidemiology study like malaria, one can adopt different equations to formulate the problem.Alternatively, individual based modelling is started to emerge and useful for epidemiology study due to the nature of flexibility ad emergence behaviour of individual based modelling. Since various epidemiology mathematical models has been introduced and implemented, can we reuse the models in individual based modelling? In fact, it is possible but not a straightforward process. This paper presents a systematical approach for individual based epidemiology modelling and simulation by reusing the existing mathematical
models on epidemiology study.With the systematic approach, a rapidly prototyping of epidemiology study is introduced.Also, it promotes the comprehensiveness and model transformation across technical and non-technical person. |
format |
Conference or Workshop Item |
author |
Loh, Chee Wyai Nissom, Shane Cheah, Wai Shiang Jali, Nurfauza |
author_facet |
Loh, Chee Wyai Nissom, Shane Cheah, Wai Shiang Jali, Nurfauza |
author_sort |
Loh, Chee Wyai |
title |
Agent oriented methodology for malaria transmission modelling and simulation |
title_short |
Agent oriented methodology for malaria transmission modelling and simulation |
title_full |
Agent oriented methodology for malaria transmission modelling and simulation |
title_fullStr |
Agent oriented methodology for malaria transmission modelling and simulation |
title_full_unstemmed |
Agent oriented methodology for malaria transmission modelling and simulation |
title_sort |
agent oriented methodology for malaria transmission modelling and simulation |
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2017 |
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http://repo.uum.edu.my/22819/1/ICOCI%202017%20160-166.pdf http://repo.uum.edu.my/22819/ http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap03e/PID51-160-166e.pdf |
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