Application of Neural Network Pattern Recognition to Discriminating the Production Conditions of Bacillus Thuringiensis

Artificial neural network pattern recognition was applied to discriminating the solid state fermentation conditions of Bacillus thuringiensis. The neural network was constitute of three layers and the back propagation algorithm was used. To evaluate the performence of the networks, the Cross Validation strategy was employed and satisfactory results was obtained. It was showed that neural network pattern recognition approach was quite promising in the optimization of fermentation conditions.