Modeling environmental noise exceedances using non-homogeneous Poisson processes

In this work a non-homogeneous Poisson model is considered to study noise exposure. The Poisson process, counting the number of times that a sound level surpasses a threshold, is used to estimate the probability that a population is exposed to high levels of noise a certain number of times in a give...

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Published inThe Journal of the Acoustical Society of America Vol. 136; no. 4; p. 1631
Main Authors Guarnaccia, Claudio, Quartieri, Joseph, Barrios, Juan M, Rodrigues, Eliane R
Format Journal Article
LanguageEnglish
Published United States 01.10.2014
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Abstract In this work a non-homogeneous Poisson model is considered to study noise exposure. The Poisson process, counting the number of times that a sound level surpasses a threshold, is used to estimate the probability that a population is exposed to high levels of noise a certain number of times in a given time interval. The rate function of the Poisson process is assumed to be of a Weibull type. The presented model is applied to community noise data from Messina, Sicily (Italy). Four sets of data are used to estimate the parameters involved in the model. After the estimation and tuning are made, a way of estimating the probability that an environmental noise threshold is exceeded a certain number of times in a given time interval is presented. This estimation can be very useful in the study of noise exposure of a population and also to predict, given the current behavior of the data, the probability of occurrence of high levels of noise in the near future. One of the most important features of the model is that it implicitly takes into account different noise sources, which need to be treated separately when using usual models.
AbstractList In this work a non-homogeneous Poisson model is considered to study noise exposure. The Poisson process, counting the number of times that a sound level surpasses a threshold, is used to estimate the probability that a population is exposed to high levels of noise a certain number of times in a given time interval. The rate function of the Poisson process is assumed to be of a Weibull type. The presented model is applied to community noise data from Messina, Sicily (Italy). Four sets of data are used to estimate the parameters involved in the model. After the estimation and tuning are made, a way of estimating the probability that an environmental noise threshold is exceeded a certain number of times in a given time interval is presented. This estimation can be very useful in the study of noise exposure of a population and also to predict, given the current behavior of the data, the probability of occurrence of high levels of noise in the near future. One of the most important features of the model is that it implicitly takes into account different noise sources, which need to be treated separately when using usual models.
Author Guarnaccia, Claudio
Quartieri, Joseph
Barrios, Juan M
Rodrigues, Eliane R
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  givenname: Juan M
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  organization: Facultad de Ciencias, Universidad Nacional Autónoma de México, 04510 Ciudad de México, Federal District, Mexico
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  givenname: Eliane R
  surname: Rodrigues
  fullname: Rodrigues, Eliane R
  organization: Instituto de Matemáticas, Universidad Nacional Autónoma de México, 04510 Ciudad de México, Federal District, Mexico
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