Predicting and identifying traffic hot spots applying neuro-fuzzy systems in intercity roads

International Journal of Environmental Science and Technology

Volumn 6, Issue 2, 2009, Pages 309-314

  Hosseinlou, M Hadji ^a   Sohrabi, M ^a  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Accident; Back propagation; Hybrid; Least square; Optimization; Safety; Sugeno

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; CURVE FITTING; FORECASTING; FUZZY INFERENCE; FUZZY LOGIC; FUZZY SYSTEMS; INFERENCE ENGINES; INTEGRATED OPTICS; MOTOR TRANSPORTATION; OPTIMIZATION; ROADS AND STREETS;

ACCIDENT DATUM; ACCIDENT FACTORS; ACCIDENT FREQUENCIES; ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMS; AMBIGUOUS DATUM; ECONOMIC LOSS; FALSE NEGATIVES; FUZZY INFERENCE SYSTEMS; HOT SPOTS; HUMAN ASSETS; HYBRID; HYBRID OPTIMIZATIONS; INTEGRATED SYSTEMS; LEAST SQUARE; MAKING DECISIONS; NEURO-FUZZY SYSTEMS; RESEARCH METHODS; ROAD SAFETIES; SAFETY; SUGENO; SUGENO TYPES;

ACCIDENTS;

ACCIDENT; BACK PROPAGATION; DECISION MAKING; FUZZY MATHEMATICS; LEAST SQUARES METHOD; NUMERICAL MODEL; OPTIMIZATION; ROAD TRANSPORT; SOCIOECONOMIC IMPACT; TRAFFIC MANAGEMENT; TRANSPORTATION SAFETY;

ASIA; EURASIA; IRAN; MIDDLE EAST; TEHRAN [IRAN];

EID: 63449107753     PISSN: 17351472     EISSN: 17352630     Source Type: Journal    
DOI: 10.1007/BF03327634     Document Type: Review

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