title: Assessment of traffic noise levels in urban areas using different soft computing techniques.
abstract: Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.
authors: School of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, Belgrade, Serbia.
authors: J
authors: J
authors: Tomić
authors: Faculty of Mechanical and Civil Engineering, University of Kragujevac, Dositejeva 19, Kraljevo, Serbia tomic.j@mfkv.kg.ac.rs, bogojevic.n@mfkv.kg.ac.rs, pljakic.m@mfkv.kg.ac.rs, dsumarac@etf.bg.ac.rs.
authors: N
authors: N
authors: Bogojević
authors: Faculty of Mechanical and Civil Engineering, University of Kragujevac, Dositejeva 19, Kraljevo, Serbia tomic.j@mfkv.kg.ac.rs, bogojevic.n@mfkv.kg.ac.rs, pljakic.m@mfkv.kg.ac.rs, dsumarac@etf.bg.ac.rs.
authors: M
authors: M
authors: Pljakić
authors: School of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, Belgrade, Serbia.
authors: D
authors: D
authors: Šumarac-Pavlović