The 1 ST international conference on electronics, artificial intelligence and technologies ICEAINT 2021

Permanent URI for this collection

Now showing 1 - 1 of 1

Predictive modeling of Young's modulus for alpha alumina using artificial neural network and multiple linear regression
(University of Oum El Bouaghi, 2021) Fissah, Belgacem; Belghalem, Hadj; Djaddou, Messaoud
In the present work, we have constructed a predictive model for one of the important mechanical properties in the study of the mechanical and thermal behavior of materials, this property is Young's modulus. The samples on which the experiments to determine the above property of alumina (α-Al2O3) were performed were made by Spark Plasma Sintering (SPS). The experimental results were exploited using the radial basis function (RBF) neural network model and multiple linear regression (MLR) to predict and construct the mathematical model. A comparison was made of the multiple linear regression model with the radial basis function (RBF) neural network model. Then, the two proposed models were compared with the experimental results. The study obtained showed good agreement between the experimental results and the proposed RBFNN models. But the MLR models were modest in predicting the studied mechanical property.