The influence of number of the training patterns on errors, which occur in an artificial neural network was analyzed. The training patterns were used while predicting the odour intensity based on hypothetical chromatograms. The trainings of artificial neural network were conducted on the basis of chromatograms of air samples containing three odorants and five odourless compounds. Fifty patterns were used, what enabled to achieve 96% of correct answers in tests.