Radial
Basis Function Network versus Regression Model in Manufacturing Processes
Prediction by Homero De Jesus De Leon Delgado* in Open Access Biostatistics& Bioinformatics
One
of the objectives of manufacturing industry, is to increase the efficiency in
their processes using different methodologies, such as statistical modeling,
for production control and decision-making. However, the classical tools
sometimes have difficulty to depict the manufacturing processes. This paper is
a comparative study between a multiple regression model and a Radial Basis
Function Neural Network in terms of the statistical metrics R2 and R2 adj
applied in a permanent mold casting process and TIG welding process. Results
showed that in both cases, the RBF network performed better than Regression
model.
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