Comparison of classical statistical methods and artificial neural network in traffic noise prediction

Environmental Impact Assessment Review

Volumn 49, Issue , 2014, Pages 24-30

  Nedic, Vladimir ^a   Despotovic, Danijela ^a   Cvetanovic, Slobodan ^b   Despotovic, Milan ^a   Babic, Sasa ^c  

^a UNIVERSITY OF KRAGUJEVAC   (Serbia)

^b UNIVERSITY OF NI   (Serbia)

^c Faculty of Economics University of Niš Trg kralja Aleksandra Ujedinitelja ^*  (Serbia)

Author keywords

Artificial neural network; Optimization; Software; Traffic noise

Indexed keywords

ACOUSTIC NOISE MEASUREMENT; COMPUTER SOFTWARE; FORECASTING; NEURAL NETWORKS; NOISE POLLUTION; OPTIMIZATION; REGRESSION ANALYSIS; TRAFFIC CONTROL;

CALCULATED VALUES; CLASSICAL METHODS; COMPARATIVE ANALYSIS; LABOR PRODUCTIVITY; TRAFFIC NOISE; TRAFFIC NOISE LEVELS; URBAN ENVIRONMENTS; USER-FRIENDLY-SOFTWARE;

ACOUSTIC NOISE;

ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; HEALTH RISK; MENTAL HEALTH; NOISE POLLUTION; NUMERICAL MODEL; OPTIMIZATION; POLLUTANT SOURCE; PREDICTION; SOFTWARE; URBAN POLLUTION;

EID: 84904268330     PISSN: 01959255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eiar.2014.06.004     Document Type: Article

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