abstract
This study has investigated the utility and potential advantages of an artificial intelligence technology –
neurofuzzy logic – as a modeling tool to study direct compression formulations. The modeling perfor-
mancewas comparewith traditional statistical analysis. Fromresults it can be stated that the normalized
error obtained fromneurofuzzy logicwas lower. Compared to the multiple regression analysis neurofuzzy
logic showed higher accuracy in prediction for the five outputs studied.
Rule sets generated by neurofuzzy logic are completely in agreement with the findings based on sta-
tistical analysis and advantageously generate understandable and reusable knowledge. Neurofuzzy logic
is easy and rapid to apply and outcomes provided knowledge not revealed via statistical analysis.
lusions from a databa