Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-16
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Due to the growing number of vehicles using the national road networks that link major urban centers, traffic noise is becoming a major issue in relation to the transportation system.
Thus, it is important to determine noise model parameters to predict road traffic noise levels as part of an environmental assessment, according to traffic volume and pavement surface type.
To determine the parameters of a noise prediction model, statistical pass-by and close proximity tests are required.
This paper provides a parameter determination procedure for noise prediction models through an adaptive particle filter (PF) algorithm, based on using a weigh-in-motion system, which obtains vehicle velocities and types, as well as step-up microphones, which measure the combined noises emitted by various vehicle types.
Finally, an evaluation of the adaptive noise parameter determination algorithm was carried out to assess the agreement between predictions and measurements.
American Psychological Association (APA)
Cho, Hyun-Tae& Mun, Sungho. 2016. Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1112046
Modern Language Association (MLA)
Cho, Hyun-Tae& Mun, Sungho. Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm. Mathematical Problems in Engineering No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1112046
American Medical Association (AMA)
Cho, Hyun-Tae& Mun, Sungho. Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1112046
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112046