A case based reasoning system capturing fire modelling expertise

Taylor, S; Knight, B; Petridis, M; Ewer, J; Galea, E

dc.contributor.author	Taylor, S	en
dc.contributor.author	Knight, B	en
dc.contributor.author	Petridis, M	en
dc.contributor.author	Ewer, J	en
dc.contributor.author	Galea, E	en
dc.date.accessioned	2014-03-01T01:15:58Z
dc.date.available	2014-03-01T01:15:58Z
dc.date.issued	2001	en
dc.identifier.issn	13359150	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/13863
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0345774113&partnerID=40&md5=51134ff524613d5d753f6283e4e77ce3	en
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0345774113&partnerID=40&md5=51134ff524613d5d753f6283e4e77ce3	en
dc.title	A case based reasoning system capturing fire modelling expertise	en
heal.type	journalArticle	en
heal.publicationDate	2001	en
heal.abstract	This paper describes the architecture of the case based reasoning (CBR) component of Smartfire, a fire field modelling tool for use by members of the Fire Safety Engineering community who are not expert in modelling techniques. The CBR system captures the qualitative reasoning of an experienced modeller in the assessment of room geometries so as to set up the important initial parameters of the problem. The system relies on two important reasoning principles obtained from the expert: 1) there is a natural hierarchical retrieval mechanism which may be employed; and 2) much of the reasoning on a qualitative level is linear in nature, although the computational solution of the problem is non-linear. The paper describes the qualitative representation of geometric room information on which the system is based, and the principles on which the CBR system operates.	en
heal.journalName	Computing and Informatics	en
dc.identifier.volume	20	en
dc.identifier.issue	3	en
dc.identifier.spage	269	en
dc.identifier.epage	288	en