Yu, L. and Kang, J. (2015) Using Ann to Study Sound Preference Evaluation in Urban Open Spaces. Journal of Environmental Engineering and Landscape Management, 23 (3). 163 - 171. ISSN 1648-6897
Abstract
In soundscape research, subjective preference evaluation of a sound is crucial. Based on a series of field studies and laboratory experiments, influence of sound category and psychoacoustic parameters on sound preference evaluation is examined. It has been found that sound category and loudness and sharpness are important. Regarding a previous study, age and education level are also important to influence sound preference evaluation. In order to understand user's preference in terms of sound at a design stage, prediction of sound preference evaluation is essential. As sound preference evaluation is complicated and influenced by various factors linearly and non-linearly, artificial neural network (ANN) has been explored to make predictions of sound preference evaluation. A number of developed ANN models have been demonstrated, and it has been found that the models including input factors of sound category, loudness and sharpness produce better predictions than others. The best prediction model is the one that is based on an individual case study site. Based on the best prediction model, a mapping tool for sound preference evaluation has been developed and its usefulness for aiding landscape architects and urban designers has been demonstrated.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2015 Taylor & Francis. This is an author produced version of a paper subsequently published in Journal of Environmental Engineering and Landscape Management. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | sound preference evaluation; urban open space; ANN modelling |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Architecture (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 07 Oct 2015 12:55 |
Last Modified: | 31 Mar 2016 21:19 |
Published Version: | http://dx.doi.org/10.3846/16486897.2015.1050399 |
Status: | Published |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Identification Number: | 10.3846/16486897.2015.1050399 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:90629 |