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Mosquito population dynamics from cellular automata-based simulation
In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-ba...
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creator | Syafarina, Inna Sadikin, Rifki Nuraini, Nuning |
description | In this paper we present an innovative model for simulating mosquito-vector population dynamics. The
simulation consist of two stages: demography and dispersal dynamics. For demography
simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular
automata-based model for simulating dispersal of the vector. In simulation, each
individual vector is able to move to other grid based on a random walk. Our model is also capable to
represent immunity factor for each grid. We simulate the model to evaluate its
correctness. Based on the simulations, we can conclude that our model is correct. However, our
model need to be
improved to find a realistic parameters to match real data. |
doi_str_mv | 10.1063/1.4940299 |
format | conference_proceeding |
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simulation consist of two stages: demography and dispersal dynamics. For demography
simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular
automata-based model for simulating dispersal of the vector. In simulation, each
individual vector is able to move to other grid based on a random walk. Our model is also capable to
represent immunity factor for each grid. We simulate the model to evaluate its
correctness. Based on the simulations, we can conclude that our model is correct. However, our
model need to be
improved to find a realistic parameters to match real data.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/1.4940299</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><ispartof>AIP conference proceedings, 2016, Vol.1705 (1)</ispartof><rights>AIP Publishing LLC</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><contributor>Misran, Mohamad Harris</contributor><contributor>Sulaiman, Hamzah Asyrani</contributor><contributor>Saat, Mohd Shakir Md</contributor><contributor>Othman, Mohd Azlishah</contributor><contributor>Darsono, Abd Majid</contributor><contributor>Aziz, Mohamad Zoinol Abidin Abd</contributor><contributor>Aminuddin, Mai Mariam Mohamed</contributor><creatorcontrib>Syafarina, Inna</creatorcontrib><creatorcontrib>Sadikin, Rifki</creatorcontrib><creatorcontrib>Nuraini, Nuning</creatorcontrib><title>Mosquito population dynamics from cellular automata-based simulation</title><title>AIP conference proceedings</title><description>In this paper we present an innovative model for simulating mosquito-vector population dynamics. The
simulation consist of two stages: demography and dispersal dynamics. For demography
simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular
automata-based model for simulating dispersal of the vector. In simulation, each
individual vector is able to move to other grid based on a random walk. Our model is also capable to
represent immunity factor for each grid. We simulate the model to evaluate its
correctness. Based on the simulations, we can conclude that our model is correct. However, our
model need to be
improved to find a realistic parameters to match real data.</description><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2016</creationdate><recordtype>conference_proceeding</recordtype><sourceid/><recordid>eNp9j0FLxDAUhIMoWFcP_oOcha55SdM0R1l1FVa8KHgLr0kKkXZTm1TYf--qC948zWG-mWEIuQS2BFaLa1hWumJc6yNSgJRQqhrqY1IwpquSV-LtlJyl9M72iFJNQW6fYvqYQ450jOPcYw5xS91ui0OwiXZTHKj1fb93JopzjgNmLFtM3tEUhkPgnJx02Cd_cdAFeb2_e1k9lJvn9ePqZlMmzmUuvUR0VQMAzDIpa7Cy4gwF77DhnQfPJDrtvG2bxinonLIatGidcta1ohYLcvXbm2zIP8tmnMKA084AM9__DZjD___gzzj9gWZ0nfgCDqxdwg</recordid><startdate>20160201</startdate><enddate>20160201</enddate><creator>Syafarina, Inna</creator><creator>Sadikin, Rifki</creator><creator>Nuraini, Nuning</creator><scope/></search><sort><creationdate>20160201</creationdate><title>Mosquito population dynamics from cellular automata-based simulation</title><author>Syafarina, Inna ; Sadikin, Rifki ; Nuraini, Nuning</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-s225t-e5aad481110c05561c5420a32fa82fe1e05ad9decb88d71fd7c9193bd7dcdb363</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2016</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Syafarina, Inna</creatorcontrib><creatorcontrib>Sadikin, Rifki</creatorcontrib><creatorcontrib>Nuraini, Nuning</creatorcontrib></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Syafarina, Inna</au><au>Sadikin, Rifki</au><au>Nuraini, Nuning</au><au>Misran, Mohamad Harris</au><au>Sulaiman, Hamzah Asyrani</au><au>Saat, Mohd Shakir Md</au><au>Othman, Mohd Azlishah</au><au>Darsono, Abd Majid</au><au>Aziz, Mohamad Zoinol Abidin Abd</au><au>Aminuddin, Mai Mariam Mohamed</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Mosquito population dynamics from cellular automata-based simulation</atitle><btitle>AIP conference proceedings</btitle><date>2016-02-01</date><risdate>2016</risdate><volume>1705</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>In this paper we present an innovative model for simulating mosquito-vector population dynamics. The
simulation consist of two stages: demography and dispersal dynamics. For demography
simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular
automata-based model for simulating dispersal of the vector. In simulation, each
individual vector is able to move to other grid based on a random walk. Our model is also capable to
represent immunity factor for each grid. We simulate the model to evaluate its
correctness. Based on the simulations, we can conclude that our model is correct. However, our
model need to be
improved to find a realistic parameters to match real data.</abstract><doi>10.1063/1.4940299</doi><tpages>8</tpages></addata></record> |
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source | American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list) |
title | Mosquito population dynamics from cellular automata-based simulation |
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