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Volumn 36, Issue 1, 2005, Pages 97-108

Identifying crash propensity using specific traffic speed conditions

Author keywords

Crash prediction; Freeway crashes; Loop detectors; Probabilistic Neural Networks; Traffic speed

Indexed keywords

CRASHWORTHINESS; HIGHWAY ACCIDENTS; HIGHWAY SYSTEMS; NEURAL NETWORKS; PROBABILITY; SENSORS; SPEED;

EID: 14544280579     PISSN: 00224375     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jsr.2004.11.002     Document Type: Article
Times cited : (182)

References (10)
  • 1
    • 0033340740 scopus 로고    scopus 로고
    • Enhancing the universality and transferability of freeway incident detection using a Bayesian-based neural network
    • B. Abdulhai, and S. Ritchie Enhancing the universality and transferability of freeway incident detection using a Bayesian-based neural network Transportation Research Part C: Emerging Technologies 7 5 1999 261 280
    • (1999) Transportation Research Part C: Emerging Technologies , vol.7 , Issue.5 , pp. 261-280
    • Abdulhai, B.1    Ritchie, S.2
  • 5
    • 36849055023 scopus 로고    scopus 로고
    • Real-time crash prediction model for the application to crash prevention in freeway traffic
    • C. Lee, F. Saccomanno, and B. Hellinga Real-time crash prediction model for the application to crash prevention in freeway traffic Transportation Research Record 2003 1840
    • (2003) Transportation Research Record , pp. 1840
    • Lee, C.1    Saccomanno, F.2    Hellinga, B.3
  • 8
    • 0012445285 scopus 로고    scopus 로고
    • Speed and crashes: A controversial topic and an elusive relationship
    • D. Shinar Speed and crashes: A controversial topic and an elusive relationship Traffic Eng. 41 1999 52 55
    • (1999) Traffic Eng. , vol.41 , pp. 52-55
    • Shinar, D.1
  • 9
    • 0001886731 scopus 로고    scopus 로고
    • Probabilistic neural networks and general regression neural networks
    • C.H. Chen McGraw-Hill Berlin
    • D. Specht Probabilistic neural networks and general regression neural networks C.H. Chen Fuzzy Logic and Neural Network Handbook 1996 McGraw-Hill Berlin 3.1 3.37
    • (1996) Fuzzy Logic and Neural Network Handbook , pp. 31-337
    • Specht, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.