Artificial Neural Networks in Vehicular Pollution Modelling

  • Mukesh Khare
  • S. M. Shiva Nagendra

Part of the Studies in Computational Intelligence book series (SCI, volume 41)

Table of contents

About this book

Introduction

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.

Keywords

Line Source Emission Modeling Vehicular Pollution artificial neural network behavior computational intelligence control intelligence model modeling networks neural network neural networks traffic

Authors and affiliations

  • Mukesh Khare
    • 1
  • S. M. Shiva Nagendra
    • 2
  1. 1.Atlantic LNG Chair, Professor in Environmental EngineeringUniversity of West IndiesSt. AugustineTrinidad and Tobago
  2. 2.Assistant Professor in Civil EngineeringIIT MadrasChennaiIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-37418-3
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-37417-6
  • Online ISBN 978-3-540-37418-3
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book
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