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Assessing the quality of neural models using a model of flow characteristics of fabrics as an example

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Języki publikacji
EN
Abstrakty
EN
In this article, a method for assessing the quality of now-widespread neuron models is presented. Attention has been paid to the significance of analysing individual input quantities in the model constructed. Then, the parameters which are quantitative measures of the neural model's quality have to be specified. The need for structural verification of the network is stressed, which is the basis for stating that the neural model obtained has been well matched with the investigation results. The assessment of the neural model's quality has been shown, using a model of the flow characteristics of fabrics as an example.
Rocznik
Strony
162--168
Opis fizyczny
Bibliogr. 19 poz.
Twórcy
autor
  • Department for Automation of Textile Processes, Technical University of Łódź, Poland tel. +48 42 6313399 fax +48 42 6313310
Bibliografia
  • 1. Ballou J.W., Roetling J.A., High Speed Tensile Testing of Fibres, Textile Research Journal, 1958, Vol. 28, No 8, pp. 631-646.
  • 2. Box, G.E.P., Draper, N.R., Empirical Model-Building and Response Surfaces, Wiley, New York 1987.
  • 3. Brasquet C., Le Cloirec P., Pressure Drop Through Textile Fabrics – Experimental Data Modelling Using Classical Models and Neural Networks, Chemical Engineering Science, 2000, Vol. 55, No. 15, pp. 2767-2778.
  • 4. Chung-Feng J.K., Ching-Jeng L., A Back-Propagation Neural Network for Recognizing Fabric Defects, Textile Research Journal, 2003, Vol. 73, No. 2, pp. 147-151.
  • 5. Chung-Feng J.K., Ching-Jeng L., Cheng-Chih T., Using a Neural Network to Identify Fabric Defects in Dynamic Cloth Inspection, Textile Research Journal, 2003, Vol. 73, No. 3, pp. 238-244.
  • 6. Deming, S.N., Morgan, S.L., Experimental Design: A Chemometric Approach, Elsevier Sc. Pub. B.V., Amsterdam, 1993.
  • 7. Gniotek K., Dynamic Permeability of Textiles, Fibres & Textiles in Eastern Europe, 1996, Vol. 4, No. 2, pp. 54-55.
  • 8. Gniotek, K., Modelling and Measurement of Textile Objects for Experiment Design, Fibres & Textiles in Eastern Europe (ISI), 2002, No. 10, pp. 52-57.
  • 9. Gniotek, K., Controllability of Object Measured for the Need of Experiment Design, XVII IMEKO World Congress, Metrology in the 3rd Millenium, pp. 1922-1925, Dubrovnik, Croatia, 2003.
  • 10. Gniotek K., Tokarska M., Pomiary udarowej przepuszczalności powietrza płaskich wyrobów włókienniczych (in Polish), materiały V Szkoły – Konferencji Metrologia Wspomagana Komputerowo, SOWA Sp. z o.o., Tom 3, ss. 235-240, Rynia k/Warszawy, 2001.
  • 11. Gniotek, K., Tokarski, P., New Methods of Assessing Static and Dynamic Flow Characteristic of Textiles, Textile Research Journal, 2000, Vol. 70, No. 1, pp. 53-58.
  • 12. Jackowska-Strumiłło L., Jackowski T., Chylewska B., Cyniak D., Application of Hybrid Neural Model to Determination of Selected Yarn Parameters, Fibres & Textiles in Eastern Europe, 1998, Vol. 6, No. 4, pp. 27-32.
  • 13. Statistica Neural Networks PL. Poradnik użytkownika (in Polish), StatSoft Polska, 2001.
  • 14. Statistica Neural Networks PL. Przewodnik problemowy (in Polish), StatSoft Polska, 2001.
  • 15. Tadeusiewicz R., Sieci neuronowe (in Polish), Akademicka Oficyna Wydawnicza RM, Warszawa 1993.
  • 16. Tokarska, M., Application of Experiment Design Method to Fabric Impact Air-Permeability Research, proceedings of 6th International Conference of Faculty of Engineering and Marketing of Textile, Technical University, Lodz, Poland, 2003.
  • 17. Tokarska M., Neural Model of the Permeability Features of Woven Fabrics, Textile Research Journal, 2004, Vol. 74, No. 12, pp. 1045-1048.
  • 18. Tokarska M, Model of Pressure Drop on Woven Fabric, proceedings of 8th Conference of Faculty of Engineering and Marketing of Textile, Technical University, Lodz, Poland, 2005.
  • 19. Jackowska-Strumiłło L., Jackowski T., Cyniak D., Czekalski J., Neural Model of the Spinning Process for Predicting Selected Properties of Flax/Cotton Yarn Blends, Fibres & Textiles in Eastern Europe, 2004, Vol. 12, No. 4, pp. 17-21.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bcf8f571-5044-4c3e-837d-f38ce0e4506c
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