Establishing the program to predict Shirt Sizes with Fuzzy Logic

Abstract : This paper presents a program for prediction shirt size with a fuzzy logic technique. The Mamdani model is applied to a MISO fuzzy system with two inputs and one output. Neck girth and sleeve length are chosen as the primary dimensions, serving as input variables for this simulation model. In this study, fuzzy logic is used to select the size of the Min-Max rule. The IF-THEN structure is applied to execute commands effectively within this model. The outcome is an appropriate size. The program’s fuzzy rule matrix consists of 45 rows and 5 columns. Each row is a fuzzy rule. The first column represents the 9 sizes of necklaces. The second column represents the 5 groups of sleeve lengths. The third column represents the 9 predicted sizes in the output. The fourth column is the weight coefficient. The last column represents the logical connection type. The fuzzy logic approaches significantly reduces the time required. This approach provides an alternative method for prediction sizes that more accurately align with individual body measurements, offering a personalized fit.