Predicting Re-aeration Rates Using Artificial Neural Networks in Surface Aerators

Rao, Achanta Ramakrishna and Kumar, Bimlesh (2007) Predicting Re-aeration Rates Using Artificial Neural Networks in Surface Aerators. In: International Journal of Applied Environmental Sciences, 2 (1). pp. 155-166.

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Abstract

The paper illustrates the application of a neural-network model to the modeling of mass transfer in unbaffled surface aeration tank fitted with six flat bladed rotors under geometrically similar conditions. Back-propagation with Levenberg-Marquadt algorithm is used for the modeling of neural-network. This paper discusses the ability of neural-network to model the mass transfer rate in unbaffled surface aeration tank. A thorough sensitive analysis has also been made to ascertain which variables are having maximum influence on reaeration rates.

Item Type:	Journal Article
Publication:	International Journal of Applied Environmental Sciences
Publisher:	Research India Publications
Additional Information:	Copyright of this article belongs to Research India Publications
Keywords:	Levenberg-Marquadt algorithm;Neural network;Sensitivity analysis;Surface aerator;Theoretical power per unit volume
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	11 Apr 2008
Last Modified:	19 Sep 2010 04:44
URI:	http://eprints.iisc.ac.in/id/eprint/13659

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