Parameter Estimation for Traffic Noise Models Using a Harmony Search Algorithm

Autor: Deok-Soon An, Young-Chan Suh, Sungho Mun, Byung-Sik Ohm
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: Journal of Applied Mathematics, Vol 2013 (2013)
Druh dokumentu: article
ISSN: 1110-757X
1687-0042
DOI: 10.1155/2013/953641
Popis: A technique has been developed for predicting road traffic noise for environmental assessment, taking into account traffic volume as well as road surface conditions. The ASJ model (ASJ Prediction Model for Road Traffic Noise, 1999), which is based on the sound power level of the noise emitted by the interaction between the road surface and tires, employs regression models for two road surface types: dense-graded asphalt (DGA) and permeable asphalt (PA). However, these models are not applicable to other types of road surfaces. Accordingly, this paper introduces a parameter estimation procedure for ASJ-based noise prediction models, utilizing a harmony search (HS) algorithm. Traffic noise measurement data for four different vehicle types were used in the algorithm to determine the regression parameters for several road surface types. The parameters of the traffic noise prediction models were evaluated using another measurement set, and good agreement was observed between the predicted and measured sound power levels.
Databáze: Directory of Open Access Journals