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Artificial Neural Netorks in Vehicular Pollution Modelling [Hardcover]

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  • Category: Books (Mathematics)
  • Author:  Khare, Mukesh, Nagendra, S.M. Shiva
  • Author:  Khare, Mukesh, Nagendra, S.M. Shiva
  • ISBN-10:  3540374175
  • ISBN-10:  3540374175
  • ISBN-13:  9783540374176
  • ISBN-13:  9783540374176
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Feb-2006
  • Pub Date:  01-Feb-2006
  • SKU:  3540374175-11-SPRI
  • SKU:  3540374175-11-SPRI
  • Item ID: 100721440
  • List Price: $169.99
  • Seller: ShopSpell
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  • Delivery by: Jan 04 to Jan 06
  • Notes: Brand New Book. Order Now.

This book provides a step-by-step procedure for formulation and development of Artificial Neural Networks based Vehicular pollution models. It takes into account meteorological and traffic aspects. The book will be useful for professionals and researchers working in problems associated with urban air pollution management and control

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.

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

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 displS(

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