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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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|
|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|
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