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    Comparison of Fuzzy and Neural Classifiers for Road Accidents Analysis

    Source: Journal of Computing in Civil Engineering:;1998:;Volume ( 012 ):;issue: 001
    Author:
    Tarek Sayed
    ,
    Walid Abdelwahab
    DOI: 10.1061/(ASCE)0887-3801(1998)12:1(42)
    Publisher: American Society of Civil Engineers
    Abstract: This paper investigates the classification of road accidents using neural networks and fuzzy classification techniques. Accident correctability by road improvements has been advocated as an important criterion in the identification of accident-prone locations. Sayed et al. (1995) described a method to identify accident correctability using a fuzzy classification algorithm (fuzzy
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      Comparison of Fuzzy and Neural Classifiers for Road Accidents Analysis

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    http://yetl.yabesh.ir/yetl1/handle/yetl/42929
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    contributor authorTarek Sayed
    contributor authorWalid Abdelwahab
    date accessioned2017-05-08T21:12:43Z
    date available2017-05-08T21:12:43Z
    date copyrightJanuary 1998
    date issued1998
    identifier other%28asce%290887-3801%281998%2912%3A1%2842%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/42929
    description abstractThis paper investigates the classification of road accidents using neural networks and fuzzy classification techniques. Accident correctability by road improvements has been advocated as an important criterion in the identification of accident-prone locations. Sayed et al. (1995) described a method to identify accident correctability using a fuzzy classification algorithm (fuzzy
    publisherAmerican Society of Civil Engineers
    titleComparison of Fuzzy and Neural Classifiers for Road Accidents Analysis
    typeJournal Paper
    journal volume12
    journal issue1
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)0887-3801(1998)12:1(42)
    treeJournal of Computing in Civil Engineering:;1998:;Volume ( 012 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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