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dc.contributor.author김성호-
dc.date.accessioned2020-10-26T05:37:15Z-
dc.date.available2020-10-26T05:37:15Z-
dc.date.issued2004-11-
dc.identifier.citation대한토목학회논문집, v.24, No.6D, Page.839-844en_US
dc.identifier.issn1015-6348-
dc.identifier.urihttp://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE01223786&language=en-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/154878-
dc.description.abstractWhen the number of reported accidents to evaluate the safety of intersections is insufficient, we can use the traffic conflict technique. However, It raises a problem related to the variation of individual surveyor's recognition. This paper, to reduce the variation of individual surveyor's recognition, uses the Fuzzy Neural Network System(FNN). It is made up of a Fuzzy which is used to reduce the human obscurity, and a Neural Network System which is used to abstract, learn and memorize the certain events like the activity of human brain. At the result, the proposed model of this paper showed that it reduced the variation of surveyor's recognition until about 70 percentiles and could construct a more accurate traffic conflict model.en_US
dc.language.isoko_KRen_US
dc.publisher대한토목학회en_US
dc.subjecttraffic conflict techniqueen_US
dc.subjectvariation of recognitionen_US
dc.subjectobscurityen_US
dc.subjectfuzzy and neural network systemen_US
dc.title퍼지뉴럴네트워크를 이용한 상충데이터 정제기법 연구en_US
dc.title.alternativeA Study of the Refined Method of Conflicts Data with Fuzzy-Neural Networks Systemen_US
dc.typeArticleen_US
dc.relation.journal대한토목학회논문집-
dc.contributor.googleauthor장명순-
dc.contributor.googleauthor김성호-
dc.contributor.googleauthor김원철-
dc.contributor.googleauthor최재원-
dc.relation.code2012100412-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF ENGINEERING SCIENCES[E]-
dc.sector.departmentDEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING-
dc.identifier.pidseongho-
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COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > TRANSPORTATION AND LOGISTICS ENGINEERING(교통·물류공학과) > Articles
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