Boosting Data Management Using Artificial Neural Networks

The present work promotes the study of artificial neural networks (ANN) in the management of data from logistics chains. The main aspects and advantages of applying this technology to business are reviewed. Through a literature review, the business domains, models, algorithms and benefits of ANN forecasting are determined. A case study is generated with historical data to predict with ANN the flow of cargo moving by land and sea transport during the year 2020. The results are analyzed and when compared with the company’s actual data and the least squares method, they show greater efficiency when using ANN. Finally, conclusions are drawn on the advantages of incorporating this technology in a public company and the need to generate more research in this area to reduce costs, increase process efficiency and improve decision making.