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＜電子ブック＞
Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies / by Eliane Regina Rodrigues, Jorge Alberto Achcar
(SpringerBriefs in Mathematics. ISSN:21918201)

版	1st ed. 2013.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2013
本文言語	英語
大きさ	X, 107 p. 12 illus : online resource
著者標目	*Rodrigues, Eliane Regina author Achcar, Jorge Alberto author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Environmental monitoring LCSH:Pollution FREE:Probability Theory FREE:Environmental Monitoring FREE:Pollution
一般注記	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 HTTP:URL=https://doi.org/10.1007/978-1-4614-4645-3

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