PLASTİK ENJEKSİYON KALIPLAMADA ISKARTA ORANI TAHMİNİNDE YAPAY SİNİR AĞLARI VE ÇOKLU DOĞRUSAL REGRESYON MODELLERİN KARŞILAŞTIRILMASI

In today s global competitive environment, it is important to be able to evaluate the efficient use of a firms resources. The aim of this study is to predict the discard rate for headlight frames before the project of an automotive sub-industry firm in Bursa. For this prediction, the multilayer perceptron model, the radial basis function network model and multiple linear regression models were used. Matlab R2010b software was used for the multilayer perceptron model and radial basis function network solutions, and SPSS 13 packet software was used to solve the multiple linear regressions. Comparing the three models, the multilayer perceptron model was identified as the best predictive model.

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