Applying Fuzzy Logic and Neural Networks to Total Hand Evaluation of Knitted Fabrics

Abstract

This study of two new total hand simulating methods for knits uses fuzzy theory and neural networks. One method, a neural network system trained with a back-propaga tion algorithm, performs functional mapping between mechanical properties and the resulting total hand values of the fuzzy predicting method. The second method, a fuzzy-neural network system, uses the fuzzy membership function, weighted factor vector, and error back-propagation algorithm. The principal mechanical properties of stretchiness, bulkiness, flexibility, distortion, weight, and surface roughness of the knitted fabrics are correlated with experimentally determined Kawabata total hand values and fuzzy transformed overall hand values. Fuzzy and neural networks agree better with the subjective test results than the KES-FB system. The mechanical prop erties are fuzzified by fuzzy membership functions, then trained to predict the total hand value of outerwear knitted fabrics. In each case, the prediction error is less than the standard deviation of experimentation, and the optimum structure is investigated. These two systems, which use the Pascal programming language, produce objective ratings of outerwear knit fabrics.

Sensory and Physiological Issues

“…In the validation, the results show that the proposed network also predicts the hand of linen and silk. Another work for predicting fabric hand from physical measures has been done by combining fuzzy logic and neural networks (Park et al, 2000). The obtained results revealed that the neural networks and fuzzy logic provide an alternative approach for predicting sensory properties from instrumental measurements of fabrics.…”

Artificial Neural Networks and Their Applications in the Engineering of Fabrics

“…The prediction of the fabric hand is a complex, highly non-linear problem and therefore an early target for the application of ANNs (Youssefi & Faez, 1999;Hui et al, 2004;Shyr et al, 2004;Matsudaira, 2006). The data from the FAST system were used to approach the hand of the fabrics (Sang-Song & Tsung- , while fuzzy logic has been combined with ANN for the evaluation of the fabric hand (Park et al, 2000;Park et al, 2001). ANNs in combination with fuzzy logic have been used in the case of the prediction of the sensory properties of the fabrics, as well (Jequirim et al, 2009).…”

A linguistic multi-criteria group decision support system for fabric hand evaluation

“…Some research has therefore explored the relationship between objective and sensory fabric hand evaluations (Hu et al 1993;Park et al 2000). However, we consider that sensory and objective evaluations are two complementary information sources on a FHE and there certainly some information is lost if we replace one by the other.…”