1. F I D,Donghua University,Shanghai ， China ， 2006 Weiyuan Zhang ， 2006

2. Campus of Donghua University in Songjiang district,Shanghai

4. Fashion Institute of Design, Donghua University,Shanghai

5. Application of Genetic Algorithm to Study the Comfort of Waterproof Breathable Fabric Weiyuan zhang,Yan liu,Xiangling Meng Donghua University,Shanghai,2006 2007 Beltwide Cotton Conferences "Equipping for Excellence"

6. Outline  Abstract  Introduction  Experimental  Objective Experimental  Subjective Experimental  Comfort Model  Discussion and Conclusions

7. Abstract  An appraisal model based on genetic algorithms has been developed and applied to the comfort of different kinds of waterproof breathable fabrics on the basis of subjective and objective experimental measurements.  Comparison of the results with real tests shows excellent agreement.  Using the appraisal model we can predict the comfort class of garment made of different kinds of breathable waterproof fabrics in different dressing conditions based on the objective testing indexes.

8. This paper  Two indexes thermal insulating value and moist insulating value.  used in the objective tests, thermal insulating value and moist insulating value.  Three wear trials:  Resting, ExercisingRainy  Resting, Exercising and Rainy Procedures  Fabrics properties may not really reflect their final performance on the garments,Three wear trial permit testing more closely to actual wear. three mathematical simulations of comfort evaluation  Develop three mathematical simulations of comfort evaluation of waterproof breathable by Genetic Algorithm

9. Outline  Abstract  Introduction  Experimental  Objective Experimental  Subjective Experimental  Comfort Model  Discussion and Conclusions

10. Experimental  Objective Experimental  Materials ( Table 1 to table 3 )  Five high density fabrics  Four coated fabrics  Five laminated fabrics  One impermeable fabric  Experimental conditions: a climate chamber  Temperature : 20 ℃  Relative humidity : 35%  Air velocity : 0.1m/s  Experimental methods  JISL——WVP Water vapor penetration  LFY-217B test water pressure  Results

11. Table1 Characteristic of high density experimental fabrics Table 2 characteristic of coated experimental fabrics Objective Experimental

12. Table 3 characteristic of laminated experimental fabrics Objective Experimental

13. Results of objective experimental Table 4 Testing Results of experimental fabrics

14. Fig 1 Testing results （ I t ） of experimental fabrics  Fig 1  Shows that three types of waterproof breathable experimental fabrics have similar heat transfer property. Comparing Results

15. Fig 2 Testing results （ i m ） of experimental fabrics  Fig 2  shows the moisture transfer property ranks as follows High Density > Laminated > Coated  High Density > Laminated > Coated Comparing Results

16. Fig 3 Testing results （ WVP ） of experimental fabrics  Fig 3  shows the water vapor transfer property ranks as follows High Density > Laminated > Coated  High Density > Laminated > Coated Comparing Results

17. Fig 4 Testing results （ p ） of experimental fabrics  Fig 4  shows the waterproof ability ranks as follows  Laminated > Coated > High Density Comparing Results

18.  Subjective experimental  Materials  Seven testing garments were made of waterproof breathable fabrics shown in table 1 to 3  Experimental process  Put on the assigned raincoat  Enter the climate chamber  Appraisal  Results Sit 10m Run 10m Expose to the rain 10m rate

19. Results of subjective experimental Table 6 Appraisal Results of testing garments Table 5 Appraisal ruler(thermal,wetness and overall comfort) 1: extremely discomfort; 5: extremely comfort 123 4 5

20. Comfort Model  Introduction of Genetic Algorithms  Comfort Model  Appraise Model  Evaluation of the Appraise Model

21. Comfort Model  Introduction of Genetic Algorithms  Global optimization methods based on several metaphors from biological evolutions  Comfort Model  Program was written in Visual Basic 6.0  Input patterns  I t i m WVP and P  Output patterns  The comfort class

22. Table 7 Genetic terms Comfort Model

23. Appraise model  Use symbols defined as following x f y x F x F f x F y F ff （1）（1） （2）（2）（3）（3） （4）（4）

24. Fig.5 Appraise Model for Resting Procedure d ca a b c F f7 f6 f5 f1f8 f7 f4 Fig.6 Appraise Model for Running Procedure a F f6f8f9f6f4 f8 f4 f5

25. Fig. 7 Appraise Model for Rainy Procedure d c b a F f6 f5 f4 f8 f5 f3 f9 f4 f8

26. Evaluation of the Appraise Model  Six garments made of other samples  Subjective appraisal  Subjective appraisal with same testing procedure and experimental condition.  Comparison  Comparison of the predict comfort class with real tests (Fig.8,9,10)  Correlation  Correlation between real test and model predict at three states (Fig 11 & Table 8)

27. Fig.8 Comparison of predicted results with real subjective appraisal in resting procedure Comparison of the predict comfort class with real tests in resting

28. Fig.9 comparison of predicted results with real subjective appraisal in running procedure Comparison of the predict comfort class with real tests in running

29. Fig.10 Comparison of predicted results with real subjective appraisal in rainy procedure Discussion excellent agreement  Comparison of the predict comfort class with real tests shows excellent agreement Comparison of the predict comfort class with real tests in rainy

30. real testmodel predict(resting)model predict(running)model predict(rainy) Pearson Correlation 1.910(*).958(**).963(**) Sig. (2-tailed)..012.003.002 N 6666 Table 8 correlation between real test and model predict at three states  Discussion correlation significant  Obviously, the correlation between real test and model predict is significant at three states, that is resting, running and rainy. Fig.11 The scatter plot of the appraisal values between real test and model predict

31. Conclusions the genetic algorithms proposed in this paper offered a satisfactory model  From the comparison of predicted results with real subjective appraisal in three testing procedure, we can make a conclusion that the genetic algorithms proposed in this paper offered a satisfactory model to study the comfort of three types of waterproof breathable fabrics. same testing garment got different comfort evaluation result in different testing procedure  The following conclusions emerged as a result test that same testing garment got different comfort evaluation result in different testing procedure, which indicates the relationship between clothing comfort and wear condition.

32. Thank you for your attention and Questions & Suggestions are welcome always.