Artificial Neural Networks in Vehicular Pollution Modelling [electronic resource] / by Mukesh Khare, S. M. Shiva Nagendra.
Tipo de material: TextoSeries Studies in Computational Intelligence ; 41 | Studies in Computational Intelligence ; 41Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Descripción: XVI, 242 p. online resourceTipo de contenido:- text
- computer
- online resource
- 9783540374183
- SpringerLink (Online service)
- Engineering
- Artificial intelligence
- Mathematics
- Engineering mathematics
- Environmental protection
- Engineering
- Appl.Mathematics/Computational Methods of Engineering
- Artificial Intelligence (incl. Robotics)
- Automotive Engineering
- Atmospheric Protection/Air Quality Control/Air Pollution
- Applications of Mathematics
- Computational Intelligence
- 519 23
- TA329-348
- TA640-643
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 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.
ZDB-2-ENG
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