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Article: Data mining of cellular automata's transition rules

TitleData mining of cellular automata's transition rules
Authors
Issue Date2004
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.asp
Citation
International Journal Of Geographical Information Science, 2004, v. 18 n. 8, p. 723-744 How to Cite?
AbstractThis paper presents a new method to discover knowledge for geographical cellular automata (CA) by using a data-mining technique. CA have the ability to simulate complex geographical phenomena. Very few studies have been carried out on how to determine and validate the transition rules of CA from observed data. The transition rules of traditional CA are usually expressed by mathematical equations. This paper demonstrates that the explicit transition rules of CA can be automatically reconstructed through the rule induction procedure of data mining. The explicit transition rules are more intuitive to decision-makers. The transition rules are obtained by applying data-mining techniques to spatial data. The proposed method can reduce the uncertainties in defining transition rules and help to generate more reliable simulation results. © 2004 Taylor & Francis Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/89709
ISSN
2015 Impact Factor: 2.065
2015 SCImago Journal Rankings: 1.156
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLi, Xen_HK
dc.contributor.authorYeh, AGOen_HK
dc.date.accessioned2010-09-06T10:00:49Z-
dc.date.available2010-09-06T10:00:49Z-
dc.date.issued2004en_HK
dc.identifier.citationInternational Journal Of Geographical Information Science, 2004, v. 18 n. 8, p. 723-744en_HK
dc.identifier.issn1365-8816en_HK
dc.identifier.urihttp://hdl.handle.net/10722/89709-
dc.description.abstractThis paper presents a new method to discover knowledge for geographical cellular automata (CA) by using a data-mining technique. CA have the ability to simulate complex geographical phenomena. Very few studies have been carried out on how to determine and validate the transition rules of CA from observed data. The transition rules of traditional CA are usually expressed by mathematical equations. This paper demonstrates that the explicit transition rules of CA can be automatically reconstructed through the rule induction procedure of data mining. The explicit transition rules are more intuitive to decision-makers. The transition rules are obtained by applying data-mining techniques to spatial data. The proposed method can reduce the uncertainties in defining transition rules and help to generate more reliable simulation results. © 2004 Taylor & Francis Ltd.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.aspen_HK
dc.relation.ispartofInternational Journal of Geographical Information Scienceen_HK
dc.titleData mining of cellular automata's transition rulesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1365-8816&volume=18&issue=8&spage=723&epage=744&date=2004&atitle=Data+Mining+of+Cellular+Automata%27s+Transition+Rulesen_HK
dc.identifier.emailYeh, AGO: hdxugoy@hkucc.hku.hken_HK
dc.identifier.authorityYeh, AGO=rp01033en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/13658810410001705325en_HK
dc.identifier.scopuseid_2-s2.0-9744232197en_HK
dc.identifier.hkuros107731en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-9744232197&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume18en_HK
dc.identifier.issue8en_HK
dc.identifier.spage723en_HK
dc.identifier.epage744en_HK
dc.identifier.isiWOS:000225296700001-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLi, X=34872691500en_HK
dc.identifier.scopusauthoridYeh, AGO=7103069369en_HK
dc.identifier.citeulike41763-

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