@inproceedings{
 title = {Fuzzy Analytical Hierarchy Process Methods for Evaluating the Comfort of Textiles},
 type = {inproceedings},
 year = {2015},
 pages = {502-505},
 websites = {http://ieeexplore.ieee.org/document/7263621/},
 month = {6},
 publisher = {IEEE},
 id = {b7faf14b-5b5c-36ed-8e12-997d5f708ff5},
 created = {2016-10-19T14:49:00.000Z},
 file_attached = {true},
 profile_id = {4b66b327-35ad-3956-a9a2-307331dd9988},
 last_modified = {2021-11-23T16:32:07.307Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Wang2015},
 private_publication = {false},
 abstract = {Because there are many indexes when evaluating the performance of clothing fabrics, the method used widely is analytic hierarchy process (AHP). However, they often neglect the fuzziness when people give the intensity of importance on an absolute scale, selecting one index with membership of one and rejecting one index with membership of zero. In this experiment, we used the Fuzzy Analytic Hierarchy Process to express brain cognition and evaluate the synthesis performance of fabrics. Triangular Fuzzy Numbers (TFN) replaced the crisp number of pair wise comparison matrix, and then the defuzzification process was used to establish fuzzy vectors, through which the final result was obtained by applying the fuzzy relation composite theory. The results showed that the tested fabric belonged to the good degree, membership at 41.0%. The combination of AHP and fuzzy decision was an efficient way to tackle uncertain problem and design intelligent wearable devices.},
 bibtype = {inproceedings},
 author = {Yuyang, Wang and Luyan, Xu and Yan, Hong and Yuqing, Liu},
 doi = {10.1109/ICMTMA.2015.128},
 booktitle = {2015 Seventh International Conference on Measuring Technology and Mechatronics Automation}
}

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However, they often neglect the fuzziness when people give the intensity of importance on an absolute scale, selecting one index with membership of one and rejecting one index with membership of zero. In this experiment, we used the Fuzzy Analytic Hierarchy Process to express brain cognition and evaluate the synthesis performance of fabrics. Triangular Fuzzy Numbers (TFN) replaced the crisp number of pair wise comparison matrix, and then the defuzzification process was used to establish fuzzy vectors, through which the final result was obtained by applying the fuzzy relation composite theory. The results showed that the tested fabric belonged to the good degree, membership at 41.0%. 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However, they often neglect the fuzziness when people give the intensity of importance on an absolute scale, selecting one index with membership of one and rejecting one index with membership of zero. In this experiment, we used the Fuzzy Analytic Hierarchy Process to express brain cognition and evaluate the synthesis performance of fabrics. Triangular Fuzzy Numbers (TFN) replaced the crisp number of pair wise comparison matrix, and then the defuzzification process was used to establish fuzzy vectors, through which the final result was obtained by applying the fuzzy relation composite theory. The results showed that the tested fabric belonged to the good degree, membership at 41.0%. 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