Abstract
In the present paper, a dryness prediction model for commercial use is proposed for reducing human power and for higher quality. The proper dryness to be provided to a particular raw material is predicted before drying. And based on that proper dryness, necessary drying time in a suitable set of drying conditions is also predicted. The model for predicting dryness is built as a fuzzy linguistic model using weight or fatness and desirable hardness of product as the IF-part variables and relative weight of product as a THEN-part variable. One of the major advantages of the present system is that it needs relatively small number of rules, to be concrete, only nine rules. This idea for reducing fuzzy rules can be applicable to other systems. A multiple regression analysis model is employed for predicting necessary drying time, using nature of material, dryness predicted by the above fuzzy model, and drying conditions applied as variables.
Simulations and experiments showed very good coincidence.
