**5. The relationship between the subjective evaluation and objective measurement of fabric handle**

The subjective evaluation of fabrics leads to a set of linguistic terms strongly related to consumer preference but difficult to be quantized. It depends on many elements from raw materials to finishing processes. However, this evaluation restricts the scientific understanding of fabric performance for those who wish to design high-quality fabrics by engineering means. In the industry, the subjective evaluation is one of the main causes of conflict between producers and consumers on quality of products. Therefore, it is necessary to develop a normalized criterion representing the subjective evaluation or to replace it by an objective evaluation method. From any existing method of objective fabric evaluation, a set of precise quantitative data describing the fabric hand can be obtained but their relationship with the subjective evaluation is not completely discovered. Research has been done for modeling this relationship (Zeng & Koehl, 2003; as cited in Kawabata, 1996; as cited in Hu, 1993). However, progress in this field is rather slow because of the existence of uncertainties and imprecision in subjective linguistic expressions and the lack of mathematical models that constitute a nonlinear complex system for explaining the relationship between subjective and objective data, that, where no mathematical models are available (Zeng & Koehl, 2003).

Numerous methods such as Steven`s law, rank correlation, linear regression model, multiplefactor analysis, weighted euclidean distance, component analysis, decision and information theory, canonical correlation methods and as intelligent techniques fuzzy logic–based methods, neural network statistical models and mathematical models have been introduced for the generation of a quantitative criterion characterizing the quality of textile products and modeling relationships between the subjective fabric hand evaluation and objective numerical data. Since all these methods require tedious computations and are thus inappropriate for providing quick responses to consumers, in recent works fuzzy comprehension evaluation, neural network aggregation of data, classification methods are widely used. Advantages of these techniques can be stated as computing with numerical data and words, computing with uncertainty and imprecision, taking into account nonlinear correlation, computing with few numbers of data (Bishop, 1996; Hui et al., 2004; Bakar, 2004).

The modeling and the simulation of textile fabrics represent an important field of scientific research. Several disciplines involve in this field, such as mathematics, mechanics, physics,

Sensorial Comfort of Textile Materials 263

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