Use este identificador para citar ou linkar para este item: http://hdl.handle.net/1843/76413
Tipo: Artigo de Periódico
Título: Evaluation of artificial neural networks and the ARIMA model applied to temperature prediction in a charcoal oven
Autor(es): Rogério Santos Maciel
Nilton Alves Maia
Maurílio José Inácio
Fernando Colen
Sidney Pereira
Luiz Henrique de Souza
Resumo: This work used the Artificial Neural Networks RBF- Radial Basis Function and MLP- Multilayer Perceptron, the Neurofuzzy ANFIS- Adaptive-network-based Fuzzy Inference System and the model ARIMA-Auto Regressive Integrated Moving Average, to predict the temperature. Different topologies were tested for Artificial Neural Networks and also for Neurofuzzy, in order to find the best configuration. To evaluate the performance of the predictors, the following metrics were used: Root Mean Square Error - RMSE, Mean Square Error - MSE and Mean Absolute Error - MAE. The analysis of the quality of the predictors was also performed using Theil's U coefficient. Analyzing the results of this study, it was possible to verify that the Artificial Neural Networks, the Neurofuzzy Network and the ARIMA model, can be applied to predict the temperature in charcoal kilns, with the MLP and ANFIS networks presenting the best results.
Assunto: Redes neurais (Computação)
Carvão vegetal
Controle de temperatura
Idioma: eng
País: Brasil
Editor: Universidade Federal de Minas Gerais
Sigla da Instituição: UFMG
Departamento: ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
Tipo de Acesso: Acesso Aberto
URI: http://hdl.handle.net/1843/76413
Data do documento: 2023
metadata.dc.url.externa: http://www.ijern.com/journal/2023/March-2023/04.pdf
metadata.dc.relation.ispartof: International Journal of Education and Research
Aparece nas coleções:Artigo de Periódico



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