Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies

Name: Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies
SKU: 20352611
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Springerbriefs in Mathematics

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In this brief we consider some stochastic models that may be used to study problems related to environmental matters, in particular, air pollution. The impact of exposure to air pollutants on people's health is a very clear and well documented subject. Therefore, it is very important to obtain ways to predict or explain the behaviour of pollutants in general. Depending on the type of question that one is interested in answering, there are several of ways studying that problem. Among them we may quote, analysis of the time series of the pollutants' measurements, analysis of the information obtained directly from the data, for instance, daily, weekly or monthly averages and standard deviations. Another way to study the behaviour of pollutants in general is through mathematical models. In the mathematical framework we may have for instance deterministic or stochastic models. The type of models that we are going to consider in this brief are the stochastic ones.

Release date Australia

September 1st, 2012

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Audience

Professional & Vocational

Illustrations

12 Illustrations, black and white; X, 107 p. 12 illus.

Pages

107

Series

Springerbriefs in Mathematics

Dimensions

156x234x6

ISBN-13

9781461446446

Product ID

20352611

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Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies

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