Abstract:

The article focuses on the prediction of apple sales of selected company by linear regression and subsequently by using neural networks. The authors find that one of the most important influences on this commodity affects self-sufficiency, which is a major source of anomaly in the market with apples, which manifests itself in 6 months, when the rising price increases and quantity sold, the price increase in the reporting period for10 consecutive years was as the same as a inflation. Prediction of apple sales in the period from June to November may be based on a neuron network with benefit, without the necessity of identifying further factors affecting the demand. In the remaining months an accurate prediction with the help of a neuron network will require the identification of factors affecting purchasing behaviour of the consumers. Created prediction model and the methodology of creation of this model could be used (under specific condition) for prediction of sales for other food commodities of selected market sector.