Artificial Neural Networks in Vehicular Pollution Modelling

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Details

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.


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

Inhalt
Vehicular Pollution.- Artificial Neutral Networks.- Vehicular Pollution ModellingConventional Aproach.- Vehicular Pollution Modelling -ANN Aproach.- Aplication of ANN based Vehicular Pollution Models.- Epilogue.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783642072222
    • Auflage Softcover reprint of hardcover 1st edition 2007
    • Sprache Englisch
    • Genre Allgemeines & Lexika
    • Lesemotiv Verstehen
    • Größe H235mm x B155mm x T15mm
    • Jahr 2010
    • EAN 9783642072222
    • Format Kartonierter Einband
    • ISBN 3642072224
    • Veröffentlichung 30.11.2010
    • Titel Artificial Neural Networks in Vehicular Pollution Modelling
    • Autor S. M. Shiva Nagendra , Mukesh Khare
    • Untertitel Studies in Computational Intelligence 41
    • Gewicht 400g
    • Herausgeber Springer Berlin Heidelberg
    • Anzahl Seiten 260

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