Demand forecast using artificial neural networks as a technological tool in company processes
DOI:
https://doi.org/10.61117/ipsumtec.v5i5.143Keywords:
Artificial neural network (ANN), Artificial intelligence (AI), Forecasting, ProcessAbstract
This study explores the use of Artificial Neural Networks (ANN) for demand forecasting in a concrete company. The primary objective was to compare the forecast accuracy achieved using ANN against traditional forecasting models currently employed by the company. The goal was to determine whether ANN could improve the accuracy of demand predictions. The methodology utilized in this study involved the development of simple multilayer perceptron network models, with data extracted from the company's existing programs.
Upon evaluating the performance of both the traditional models and ANN, it was concluded that ANN provided the most accurate demand forecasts. The results, as shown in Figure 5, confirm that the application of ANN leads to improved forecasting accuracy.
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Copyright (c) 2022 Tania Guadalupe Ramos García, Mirella Parada González, Ulises Martínez Contreras, Arturo Woocay Prieto, Laura Elizabeth Silva Leyva
This work is licensed under a Creative Commons Attribution 4.0 International License.
