£108.38

Springer - Artificial Neural Networks in Vehicular Pollution

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Description

Manage urban air pollution more effectively with this specialized technical guide. This book provides a step-by-step procedure for the formulation and development of Artificial Neural Networks (ANNs) based vehicular pollution models. By utilizing parallel computational models composed of interconnected adaptive processing units, you can achieve more accurate predictions regarding the dispersive behavior of vehicular pollutants. The content specifically addresses the complex relationship between meteorological factors and traffic aspects, providing a comprehensive framework for modeling. This resource is designed to support professionals and researchers who are tackling the challenges of air quality management and control in urban environments. Whether you are studying computational intelligence or environmental engineering, this volume offers the technical foundation needed to develop predictive models for modern pollution challenges.

Key Features

Provides a step-by-step procedure for formulating and developing Artificial Neural Networks based vehicular pollution models.

Integrates critical meteorological and traffic aspects into the modeling process for higher accuracy.

Uses parallel computational models with interconnected adaptive processing units to predict pollutant behavior.

Designed for professionals and researchers focused on urban air pollution management and control.

Part of the Studies in Computational Intelligence series (Volume 41) from Springer.

Product Specifications

Format
Paperback
Domain
Amazon UK
Release Date
30 November 2010
Listed Since
20 September 2010

Barcode

No barcode data available

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