Fitting "bad urban" roadside motor traffic sound level to skewed distribution models

Muhammad Muaz; Shiu Keung Tang; Tsair Chuan Lin; H. T. Ng

Fitting "bad urban" roadside motor traffic sound level to skewed distribution models

Muhammad Muaz, Shiu Keung Tang, Tsair Chuan Lin, H. T. Ng

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

Motor vehicular traffic sound data was collected in a "bad urban" neighborhood in Hong Kong, with the microphone placed at a window of a high-rise building overlooking the motor way. This sound-pressure level data is the one-second equivalent A-weighted sound pressure level L(Aeq,1sec). This data's histogram is fit to various skewed probability distributions, like the "generalized hyperbolic" family of distribution. The fit criteria are the "log likelihood" and the "Akaike Information Criterion" (AIC).

Original language	English
Title of host publication	INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet
Publisher	Institute of Noise Control Engineering
Publication status	Published - 1 Jan 2017
Event	46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, INTER-NOISE 2017 - Hong Kong Convention and Exhibition Centre (HKCEC), Hong Kong, Hong Kong Duration: 27 Aug 2017 → 30 Aug 2017

Conference

Conference	46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, INTER-NOISE 2017
Country/Territory	Hong Kong
City	Hong Kong
Period	27/08/17 → 30/08/17

Keywords

A-weighted sound pressure level
Akaike information criterion
Log-likelihood
Road traffic noise
Skewed probability distribution model

ASJC Scopus subject areas

Acoustics and Ultrasonics

Cite this

@inproceedings{bfea0d10740447d198a8e561f8801ec8,

title = "Fitting {"}bad urban{"} roadside motor traffic sound level to skewed distribution models",

abstract = "Motor vehicular traffic sound data was collected in a {"}bad urban{"} neighborhood in Hong Kong, with the microphone placed at a window of a high-rise building overlooking the motor way. This sound-pressure level data is the one-second equivalent A-weighted sound pressure level L(Aeq,1sec). This data's histogram is fit to various skewed probability distributions, like the {"}generalized hyperbolic{"} family of distribution. The fit criteria are the {"}log likelihood{"} and the {"}Akaike Information Criterion{"} (AIC).",

keywords = "A-weighted sound pressure level, Akaike information criterion, Log-likelihood, Road traffic noise, Skewed probability distribution model",

author = "Muhammad Muaz and Tang, {Shiu Keung} and Lin, {Tsair Chuan} and Ng, {H. T.}",

year = "2017",

month = jan,

day = "1",

language = "English",

booktitle = "INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet",

publisher = "Institute of Noise Control Engineering",

address = "United States",

note = "46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, INTER-NOISE 2017 ; Conference date: 27-08-2017 Through 30-08-2017",

}

Muaz, M, Tang, SK, Lin, TC & Ng, HT 2017, Fitting "bad urban" roadside motor traffic sound level to skewed distribution models. in INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet. Institute of Noise Control Engineering, 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, INTER-NOISE 2017, Hong Kong, Hong Kong, 27/08/17.

Fitting "bad urban" roadside motor traffic sound level to skewed distribution models. / Muaz, Muhammad; Tang, Shiu Keung; Lin, Tsair Chuan et al.
INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet. Institute of Noise Control Engineering, 2017.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Fitting "bad urban" roadside motor traffic sound level to skewed distribution models

AU - Muaz, Muhammad

AU - Tang, Shiu Keung

AU - Lin, Tsair Chuan

AU - Ng, H. T.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Motor vehicular traffic sound data was collected in a "bad urban" neighborhood in Hong Kong, with the microphone placed at a window of a high-rise building overlooking the motor way. This sound-pressure level data is the one-second equivalent A-weighted sound pressure level L(Aeq,1sec). This data's histogram is fit to various skewed probability distributions, like the "generalized hyperbolic" family of distribution. The fit criteria are the "log likelihood" and the "Akaike Information Criterion" (AIC).

AB - Motor vehicular traffic sound data was collected in a "bad urban" neighborhood in Hong Kong, with the microphone placed at a window of a high-rise building overlooking the motor way. This sound-pressure level data is the one-second equivalent A-weighted sound pressure level L(Aeq,1sec). This data's histogram is fit to various skewed probability distributions, like the "generalized hyperbolic" family of distribution. The fit criteria are the "log likelihood" and the "Akaike Information Criterion" (AIC).

KW - A-weighted sound pressure level

KW - Akaike information criterion

KW - Log-likelihood

KW - Road traffic noise

KW - Skewed probability distribution model

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M3 - Conference article published in proceeding or book

BT - INTER-NOISE 2017 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet

PB - Institute of Noise Control Engineering

T2 - 46th International Congress and Exposition on Noise Control Engineering: Taming Noise and Moving Quiet, INTER-NOISE 2017

Y2 - 27 August 2017 through 30 August 2017

ER -

Fitting "bad urban" roadside motor traffic sound level to skewed distribution models

Abstract

Conference

Keywords

ASJC Scopus subject areas

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