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Rough Sets Approach in Analysis of Yarn Friction Properties

Year 2016, Volume: 9 Issue: 1, 75 - 86, 20.06.2016
https://doi.org/10.18185/eufbed.99908

Abstract

This paper was intended to analyze the frictional properties of yarns using Rough sets theory. Ten examples are investigated in this paper. The data used in this study are real data. The frictional properties (μ) of yarn samples determined in respect of four features of yarn. These features are; yarn count, raw material, twist level and production technology. One decision variable and four attributes are used as information system. ROSE2 (Rough Sets Data Explorer)  software implemented to the data set to analyze the frictional properties of yarns. As a conclusion, we concluded that raw material has the leading impact on frictional properties of yarn.

 

 

References

  • Ajayi, J. ve Elder, H., 1994. Comparative Studies of Yarn and Fabric Friction. Journal of Testing and Evaluation, 463-467.
  • Aldridge, C. H., 1999. Discerning Landslide Hazard Using a Rough Set Based Geographic Knowledge Discovery Methodology. Otago: Citeseer.
  • B.Predki, ve diğerleri, 1998. ROSE - Software Implementation of the Rough Set Theory. Lecture Notes in Artificial Intelligence, 1424, 605-608.
  • Balcıl, G. ve Sülar, V., 2016. İpliklerde Sürtünme Özelliği: Önemi ve Ölçüm Yöntemleri. Tekstil ve Mühendis, 73- 74.
  • Chattopadhyay, R. ve S., B., 1996. The Frictional Behaviour of Ring-, Rotor-, and Friction-spun Yarn. Journal of Textile Institute, 59-67.
  • Denby, E. ve Andrews, M., 1965. Friction forces on wool fibers in a worsted fabric. Textile Research J., 913-922.
  • Ghosh, A., A., P., Anandjiwala, R. ve Rengasamy, R., 2008. A Study on Dynamic Friction of Different Spun Yarns. Journal of Applied Polymer Science, 3233-3238.
  • Gupta, B. S., 2008. Friction in textile materials. Boca Raton Boston New York Washington, DC: CRC Press.
  • Hong, J., 2000. Structure-Process- Property Relationships in Polyester Spun Yarns: The Role of Fiber Friction. basım yeri bilinmiyor:Georgia Institute of Technology.
  • İnan, O., 2003. Veri madenciliği. Konya: Selçuk Üniversitesi, Fen Bilimleri Enstitüsü.
  • Institute of Computing Science, P. U. o. T., 2014. Laboratory of Intelligent Decision Support Systems. http://idss.cs.put.poznan.pl/site/rose. html [21 01 2014].
  • Kalikov, A., 2006. Veri Madenciliği ve Bir E- Ticaret Uygulaması, Yüksek Lisans Tezi, basım yeri bilinmiyor: Gazi Üniversitesi, Fen Bilimleri Enstitüsü.
  • Kalyanaraman, A. R., 1988. Yarn-Friction Studies with the SITRA Friction Measuring Device. Journal of the Textile Institute, 147-151.
  • Komorowski, J., Polkowski, L. ve Skowron, A., 1998. Rough Sets: A Tutorial. 9 dü. Singapur: Springer-Verlag.
  • Leung, Y. F. T. M. J. W. W., 2007. A rough set approach to the discovery of classification rules in spatial data. International Journal of Geographical Information Science, 21, 1033-1058.
  • Ling Peng a, b. R. N. ve diğerleri, 2014. Landslide susceptibility mapping based on rough set theory and support vector machines: A case of the Three Gorges area, China. Geomorphology, 204, 287-301.
  • Matukonis, A., Palaima, J. ve Vitkauskas, A., 1976. Material science of Textile. basım yeri bilinmiyor:Vilnius: Mokslas.
  • Morton, W. E. ve Hearle, J. W., 1962. Physical properties of. The Textile Institute, 559-590.
  • Morton, W. E. ve Hearle, J. W., 1962. Physical properties of textile fibres. The Textile Institute, 559-590.
  • Nazarov, M. ve Kamalov, R., 2010. Farklı Bağıl Nem ve Sıcaklık Koşullarında İplik Sürtünme Özelliklerinin
  • İncelenmesi. Bitirme Ödevi, İzmir: Ege
  • Üniversitesi, Mühendislik Fakültesi,
  • (https://goo.gl/5SKLqj).
  • Pan, X. ve diğerleri, 2010. A variable precision rough set approach to the remote sensing land use/cover classification. 36 dü. Geosci: Comput.
  • Pawlak, Z., 1982. Rough Sets. International Journal of Computer and Information Sciences, 11, 341-356.
  • Pawlak, Z., 1997. Rough Set Approach to Knowledge-Based Decison Support. European Journal of Operational Research, 99, 48-57.
  • Pawlak, Z., 1997. Rough Sets Approach to Knowledge Based Decision Support. European Journal of Operational Research, 99, 48-57.
  • Pawlak, Z., 1998. Rough Set Theory And Its Applications To Data Analysis. Cybernetics and Systems: An International Journal, 29(7), 661-668.
  • Pažarauskas, E., 1992. Prediction of Friction Properties of New Threads According up Today Technologies. - PhD Thesis, p. 191. Rankumar, S. ve diğerleri, 2003. Experimental Study of the Frictional Properties of Friction Spun Yarns. Journal of Applied Polymer Science, 2450-2454.
  • Schick, M., 1973. Friction and Lubrication of Synthetic Fibers. Textile Research Journal, 198-204.
  • Svetnickienė, V. ve Čiukas, R., 2006. Technical and classical yarns friction properties investigation. Mechanika, 4(60), 54-58.
  • Svetnickienė, V. ve Čiukas, R., 2006. Technical and Classical Yarns Friction Properties Investigation. Mechanika, 54-58.
  • Tay, F. ve Shen, L., 2003. Fault diagnosis based on rough set theory. Engineering Applications of Artificial Intelligence, 16, 39-43.
  • Thangavel, K. J. P. P. A. K. M., 2005. Effective classification with improved quick reduct for medical database using rough system. Bioinforma. Med. Eng., 5, 7-14.
  • Thuarisingham, B., 2003. Web Data Mining and Applications in Business Intelligence and Counter Terrorism. Boca Raton: CRC Press LLC.
  • Varža, V., 1981. Manufacturing of Wool- Polyester Yarns, Having Different Structure and Investigation of Them Properties.Kaunas.
  • Walczak, B. ve Massart, D., 1999. Rough sets theory. Chemometrics and Intelligent, 47, 1-16.
  • Walczak, B. ve Massart, D., 1999. Rough sets theory. Chemometrics and Intelligent Laboratory Systems, 47, 1-16.
  • Wegener, W. ve Shuler, B., 1964. Determination of the friction coefficient. Textilindustrie, 458-463.
  • Yin, X., Zhou, Z., Li, N. ve Chen, S., 2001. An Approach for Data Filtering Based on. Berlin: Springer-Verlag.
  • Zadeh, L. A., 1965. Fuzzy sets. Information Control, 338-353.

İplik Sürtünme Özelliklerinin İncelemesinde Kaba Kümeler Yaklaşımı

Year 2016, Volume: 9 Issue: 1, 75 - 86, 20.06.2016
https://doi.org/10.18185/eufbed.99908

Abstract

Bu çalışmada Kaba kümeler teorisi kullanılarak ipliklerin sürtünme özelliklerinin analiz edilmesi amaçlanmıştır. Çalışmada kullanılan 10 örnek veri seti gerçek verilerdir. Sürtünme özelliği olan μ ipliğin 4 özelliği tarafından belirlenmiştir. Bu özellikler; iplik numarası, hammadde, büküm sayısı ve üretim teknolojisi özellikleridir. Bu karar sisteminde 4 özellik sınıfı ve 1 karar sınıfı bulunmaktadır. İpliklerin sürtünme özelliklerini analiz etmek için Kaba kümeler teorisi için ayarlanmış olan ROSE2  yazılımı kullanılmıştır. Bu çalışma sonucunda, hammadde özellik sınıfının iplik sürtünme özellikler arasındaki en önemli özellik olduğu sonucuna varılmıştır.

References

  • Ajayi, J. ve Elder, H., 1994. Comparative Studies of Yarn and Fabric Friction. Journal of Testing and Evaluation, 463-467.
  • Aldridge, C. H., 1999. Discerning Landslide Hazard Using a Rough Set Based Geographic Knowledge Discovery Methodology. Otago: Citeseer.
  • B.Predki, ve diğerleri, 1998. ROSE - Software Implementation of the Rough Set Theory. Lecture Notes in Artificial Intelligence, 1424, 605-608.
  • Balcıl, G. ve Sülar, V., 2016. İpliklerde Sürtünme Özelliği: Önemi ve Ölçüm Yöntemleri. Tekstil ve Mühendis, 73- 74.
  • Chattopadhyay, R. ve S., B., 1996. The Frictional Behaviour of Ring-, Rotor-, and Friction-spun Yarn. Journal of Textile Institute, 59-67.
  • Denby, E. ve Andrews, M., 1965. Friction forces on wool fibers in a worsted fabric. Textile Research J., 913-922.
  • Ghosh, A., A., P., Anandjiwala, R. ve Rengasamy, R., 2008. A Study on Dynamic Friction of Different Spun Yarns. Journal of Applied Polymer Science, 3233-3238.
  • Gupta, B. S., 2008. Friction in textile materials. Boca Raton Boston New York Washington, DC: CRC Press.
  • Hong, J., 2000. Structure-Process- Property Relationships in Polyester Spun Yarns: The Role of Fiber Friction. basım yeri bilinmiyor:Georgia Institute of Technology.
  • İnan, O., 2003. Veri madenciliği. Konya: Selçuk Üniversitesi, Fen Bilimleri Enstitüsü.
  • Institute of Computing Science, P. U. o. T., 2014. Laboratory of Intelligent Decision Support Systems. http://idss.cs.put.poznan.pl/site/rose. html [21 01 2014].
  • Kalikov, A., 2006. Veri Madenciliği ve Bir E- Ticaret Uygulaması, Yüksek Lisans Tezi, basım yeri bilinmiyor: Gazi Üniversitesi, Fen Bilimleri Enstitüsü.
  • Kalyanaraman, A. R., 1988. Yarn-Friction Studies with the SITRA Friction Measuring Device. Journal of the Textile Institute, 147-151.
  • Komorowski, J., Polkowski, L. ve Skowron, A., 1998. Rough Sets: A Tutorial. 9 dü. Singapur: Springer-Verlag.
  • Leung, Y. F. T. M. J. W. W., 2007. A rough set approach to the discovery of classification rules in spatial data. International Journal of Geographical Information Science, 21, 1033-1058.
  • Ling Peng a, b. R. N. ve diğerleri, 2014. Landslide susceptibility mapping based on rough set theory and support vector machines: A case of the Three Gorges area, China. Geomorphology, 204, 287-301.
  • Matukonis, A., Palaima, J. ve Vitkauskas, A., 1976. Material science of Textile. basım yeri bilinmiyor:Vilnius: Mokslas.
  • Morton, W. E. ve Hearle, J. W., 1962. Physical properties of. The Textile Institute, 559-590.
  • Morton, W. E. ve Hearle, J. W., 1962. Physical properties of textile fibres. The Textile Institute, 559-590.
  • Nazarov, M. ve Kamalov, R., 2010. Farklı Bağıl Nem ve Sıcaklık Koşullarında İplik Sürtünme Özelliklerinin
  • İncelenmesi. Bitirme Ödevi, İzmir: Ege
  • Üniversitesi, Mühendislik Fakültesi,
  • (https://goo.gl/5SKLqj).
  • Pan, X. ve diğerleri, 2010. A variable precision rough set approach to the remote sensing land use/cover classification. 36 dü. Geosci: Comput.
  • Pawlak, Z., 1982. Rough Sets. International Journal of Computer and Information Sciences, 11, 341-356.
  • Pawlak, Z., 1997. Rough Set Approach to Knowledge-Based Decison Support. European Journal of Operational Research, 99, 48-57.
  • Pawlak, Z., 1997. Rough Sets Approach to Knowledge Based Decision Support. European Journal of Operational Research, 99, 48-57.
  • Pawlak, Z., 1998. Rough Set Theory And Its Applications To Data Analysis. Cybernetics and Systems: An International Journal, 29(7), 661-668.
  • Pažarauskas, E., 1992. Prediction of Friction Properties of New Threads According up Today Technologies. - PhD Thesis, p. 191. Rankumar, S. ve diğerleri, 2003. Experimental Study of the Frictional Properties of Friction Spun Yarns. Journal of Applied Polymer Science, 2450-2454.
  • Schick, M., 1973. Friction and Lubrication of Synthetic Fibers. Textile Research Journal, 198-204.
  • Svetnickienė, V. ve Čiukas, R., 2006. Technical and classical yarns friction properties investigation. Mechanika, 4(60), 54-58.
  • Svetnickienė, V. ve Čiukas, R., 2006. Technical and Classical Yarns Friction Properties Investigation. Mechanika, 54-58.
  • Tay, F. ve Shen, L., 2003. Fault diagnosis based on rough set theory. Engineering Applications of Artificial Intelligence, 16, 39-43.
  • Thangavel, K. J. P. P. A. K. M., 2005. Effective classification with improved quick reduct for medical database using rough system. Bioinforma. Med. Eng., 5, 7-14.
  • Thuarisingham, B., 2003. Web Data Mining and Applications in Business Intelligence and Counter Terrorism. Boca Raton: CRC Press LLC.
  • Varža, V., 1981. Manufacturing of Wool- Polyester Yarns, Having Different Structure and Investigation of Them Properties.Kaunas.
  • Walczak, B. ve Massart, D., 1999. Rough sets theory. Chemometrics and Intelligent, 47, 1-16.
  • Walczak, B. ve Massart, D., 1999. Rough sets theory. Chemometrics and Intelligent Laboratory Systems, 47, 1-16.
  • Wegener, W. ve Shuler, B., 1964. Determination of the friction coefficient. Textilindustrie, 458-463.
  • Yin, X., Zhou, Z., Li, N. ve Chen, S., 2001. An Approach for Data Filtering Based on. Berlin: Springer-Verlag.
  • Zadeh, L. A., 1965. Fuzzy sets. Information Control, 338-353.
There are 41 citations in total.

Details

Journal Section Makaleler
Authors

Caner Erden

Muhammed Nazarov This is me

Publication Date June 20, 2016
Published in Issue Year 2016 Volume: 9 Issue: 1

Cite

APA Erden, C., & Nazarov, M. (2016). Rough Sets Approach in Analysis of Yarn Friction Properties. Erzincan University Journal of Science and Technology, 9(1), 75-86. https://doi.org/10.18185/eufbed.99908