Artificial Neural Network Modeling of Water & Wastewater Treatments Processes
Author:   Ali R Khataee ,  Masoud B Kasiri
Publisher:   Nova Science Publishers Inc
ISBN:  

9781611227819


Pages:   108
Publication Date:   04 May 2011
Format:   Paperback
Availability:   In Print   Availability explained
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Artificial Neural Network Modeling of Water & Wastewater Treatments Processes


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Overview

Artificial neural networks (ANNs) are computer based systems that are designed to simulate the learning process of neurons in the human brain. ANNs have been attracting great interest during the last decade as predictive models and pattern recognition. Artificial neural networks possess the ability to ""learn"" from a set of experimental data without actual knowledge of the physical and chemical laws that govern the system. Therefore, ANNs application in data treatment is high, especially where systems present non-linearities and complex behaviour. This book describes the application of artificial neural networks for modelling of water and wastewater treatment processes.

Full Product Details

Author:   Ali R Khataee ,  Masoud B Kasiri
Publisher:   Nova Science Publishers Inc
Imprint:   Nova Science Publishers Inc
Dimensions:   Width: 23.00cm , Height: 0.90cm , Length: 15.50cm
Weight:   0.190kg
ISBN:  

9781611227819


ISBN 10:   161122781
Pages:   108
Publication Date:   04 May 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Introduction; Topology of artificial neural networks; Training, validation & test of a neural network; Applications of artificial neural network modeling; ANN modeling of adsorption processes; ANN modeling of biological treatment processes; ANN modeling of electrochemical treatment processes; ANN modeling of photocatalytic processes; ANN modeling of photooxidative processes; Conclusion; References; Index.

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