Artificial Neural Networks in Vehicular Pollution Modelling

Artificial neural networks (ANNs), which are parallel computational models, comprising of interconnected adaptive processing units (neurons) have the capability to predict accurately the dispersive behavior of vehicular pollutants under complex environmental conditions. This book aims at describing...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Khare, Mukesh (Autor), Nagendra, S.M. Shiva (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Studies in Computational Intelligence, 41
Temas:
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Automotive engineering.
Pollution.
Mathematics.
Computational intelligence.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Automotive Engineering.
Applications of Mathematics.
Computational Intelligence.
Acceso en línea:Texto Completo
Descripción
Sumario:Artificial neural networks (ANNs), which are parallel computational models, comprising of interconnected adaptive processing units (neurons) have the capability to predict accurately the dispersive behavior of vehicular pollutants under complex environmental conditions. This book aims at describing step-by-step procedure for formulation and development of ANN based VP models considering meteorological and traffic parameters. The model predictions are compared with existing line source deterministic/statistical based models to establish the efficacy of the ANN technique in explaining frequent dispersion complexities in urban areas. The book is very useful for hardcore professionals and researchers working in problems associated with urban air pollution management and control.
Descripción Física:XVI, 242 p. online resource.
ISBN:9783540374183
ISSN:1860-9503 ;

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