Overview
- Provides a step-by-step procedure for formulation and development of Artificial Neural Networks based Vehicular pollution models
- Takes into account meteorological and traffic aspects
- Useful for professionals and researchers working in problems associated with urban air pollution management and control
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 41)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (7 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Artificial Neural Networks in Vehicular Pollution Modelling
Authors: Mukesh Khare, S. M. Shiva Nagendra
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-37418-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2007
Hardcover ISBN: 978-3-540-37417-6Published: 30 October 2006
Softcover ISBN: 978-3-642-07222-2Published: 30 November 2010
eBook ISBN: 978-3-540-37418-3Published: 24 October 2006
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 242
Topics: Mathematical and Computational Engineering, Artificial Intelligence, Automotive Engineering, Atmospheric Protection/Air Quality Control/Air Pollution, Applications of Mathematics, Computational Intelligence