A common problem faced by companies working in the automotive sector is that the demand for spare parts does not usually occur continuously but intermittently, with long periods without demand. This project is focused in analyzing the different forecasting methods that are currently being used, making a comparison between them and trying to find new forecasting algorithms to improve the performance of the existing ones.
Gonzalo Atienza Lama
