Artificial neural network-genetic algorithm approach to optimize media constituents for enhancing lipase production by a soil microorganism

MA Haider, K Pakshirajan, A Singh… - Applied biochemistry and …, 2008 - Springer
MA Haider, K Pakshirajan, A Singh, S Chaudhry
Applied biochemistry and biotechnology, 2008Springer
Results of lipase production by a soil microorganism, expressed in terms of lipolytic activities
of the culture were modeled and optimized using artificial neural network (ANN) and genetic
algorithm (GA) techniques, respectively. ANN model, developed based on back propagation
algorithm, were highly accurate in predicting the system with coefficient of determination (R
2) value being close to 0.99. Optimization using GA, based on the ANN model developed,
resulted in the following values of the media constituents: 9.991 ml/l oil, 0.100 g/l MgSO 4 …
Abstract
Results of lipase production by a soil microorganism, expressed in terms of lipolytic activities of the culture were modeled and optimized using artificial neural network (ANN) and genetic algorithm (GA) techniques, respectively. ANN model, developed based on back propagation algorithm, were highly accurate in predicting the system with coefficient of determination (R 2) value being close to 0.99. Optimization using GA, based on the ANN model developed, resulted in the following values of the media constituents: 9.991 ml/l oil, 0.100 g/l MgSO4 and 0.009 g/l FeSO4. And a maximum value of 7.69 U/ml of lipolytic activity at 72 h of culture was obtained using the ANN-GA method, which was found to be 8.8% higher than the maximum values predicted by a statistical regression-based optimization technique-response surface methodology.
Springer
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