A fuzzy rule based framework for noise annoyance modeling

Predicting the effect of noise on individual people and small groups is an extremely difficult task due to the influence of a multitude of factors that vary from person to person and from context to context. Moreover, noise annoyance is inherently a vague concept. That is why, in this paper, it is a...

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Bibliographic Details
Published inThe Journal of the Acoustical Society of America Vol. 114; no. 3; p. 1487
Main Authors Botteldooren, Dick, Verkeyn, Andy, Lercher, Peter
Format Journal Article
LanguageEnglish
Published United States 01.09.2003
Subjects
Attitude
Austria
Belgium
Female
Fuzzy Logic
Health Surveys
Humans
Individuality
Male
Models, Statistical
Noise - adverse effects
Social Environment
Urbanization
Belgium
Austria
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Summary:Predicting the effect of noise on individual people and small groups is an extremely difficult task due to the influence of a multitude of factors that vary from person to person and from context to context. Moreover, noise annoyance is inherently a vague concept. That is why, in this paper, it is argued that noise annoyance models should identify a fuzzy set of possible effects rather than seek a very accurate crisp prediction. Fuzzy rule based models seem ideal candidates for this task. This paper provides the theoretical background for building these models. Existing empirical knowledge is used to extract a few typical rules that allow making the model more specific for small groups of individuals. The resulting model is tested on two large-scale social surveys augmented with exposure simulations. The testing demonstrates how this new way of thinking about noise effect modeling can be used in practice both in management support as a "noise annoyance adviser" and in social science for testing hypotheses such as the effect of noise sensitivity or the degree of urbanization.
ISSN:0001-4966
DOI:10.1121/1.1604125