Podstawowe elementy sztucznej inteligencji i przykłady ich zastosowań we włókiennictwie Część II. Przykłady zastosowań

Lewandowski, S.

Artykuł - szczegóły

Tytuł artykułu

Podstawowe elementy sztucznej inteligencji i przykłady ich zastosowań we włókiennictwie Część II. Przykłady zastosowań

Autorzy

Lewandowski S.

Identyfikatory

Warianty tytułu

Basic elements of the artificial intelligence and examples of their applications in the textile industry. Part II. Examples of applications

Języki publikacji

Abstrakty

Numerous examples of applications of the Artificial Intelligence Elements were shown in the discipline of the textile industry, with the special consideration of artificial neural networks.

Słowa kluczowe

sztuczna inteligencja włókiennictwo sztuczne sieci neuronowe

Wydawca

Wydawnictwo SIGMA-NOT

Czasopismo

Przegląd Włókienniczy - Włókno, Odzież, Skóra

Rocznik

2009

Tom

nr 8

Strony

41--45

Opis fizyczny

Bibliogr. 74 poz., rys.

Twórcy

autor

Lewandowski S.

Instytut Inżynierii Tekstyliów i Materiałów Polimerowych Akademii Techniczno- Humanistycznej w Bielsku-Białej

Bibliografia

1. Amin A. E., El-Geheni A. S., El-Hawary I. A., El-Beali R. A., 2007, Detecting the Fault from Spectrograms by Using Algorithms Techniques, Autex Research Journal, Vol. 7, No 2, s. 80-88.
2. Beltran L., Wang L., Wang X., 2004, Predicting Worsted Spinning Performance with an Artificial Neural Network Model, Textile Research Journal Vol. 74, (9), s. 757-763.
3. Beltran R., Wang L., Wang X., 2005, Predicting the Pilling Propensity of Fabrics through Artificial Neural Network Modeling, Textile Research Journal Vol. 75, (07), s. 557-561.
4. Boong Soo Jeon, Ji Hyun Bae, and Moon W. Suh, 2003. Automatic Recognition of Woven Fabric Patterns by an Artificial Neural Network, Textile Research Journal Vol. 73, (07), s. 645-650.
5. Chang-Chiun Huang, I-Chun Chen, 2001, Neural-Fuzzy Classification for Fabric Defects, Textile Research Journal. Vol. 71, (07), s. 220-224.
6. Cheng L., Adams D. L., 1995, Yarn Strength Prediction Using Neural Networks Part I: Fiber Properties and Yarn Strength Relationship, Textile Research Journal Vol.65, (09), s. 495-500.
7. Cheng. K. P. S i Lam H. L. I., 2003, Evaluating and (Comparing the Physical Properties of Spliced Yarns by Regression and Neural Network Technique, Textile Research Journal 73, (02), s. 161-164 .
8. Chiu S. H., Chcn H. M., Chen J. Y., 2001, Appearance Analysis of False Twist Textured Yarn Packages Using Image Processing and Neural Network Technology, Textile Research Journal Vol. 71, (04), s. 313-317.
9. Chung-Feng Jeffrey Kuo, Chang-Chung Wang, Chien-Teng Hsieh, 1999, Theoretical Control and Experimental Verification of Carded Web Density, Part III: Neural Network Controller Design, Textile Research Journal Vol. 69, (05), s. 401-407.
10. Chung-Feng Jeffrey Kuo, Ching-Jeng Lee i Cheng-Chih Tsai, 2003, Using a Neural Network to Identify Fabric Defects in Dynamic Cloth Inspection, Textile Research Journal Vol. 73, (03), s. 238-245.
11. Chung-Feng Jeffrey Kuo. Chung-Yang Shih, and Jiunn-Yih Lee, 2004, Automatic Recognition of Fabric Weave Patterns by a Fuzzy C-Means Clustering Method, Textile Research Journal Vol. 74, (02), s. 107-112.
12. Chung-Feng Jeffrey Kuo, Kun-Iuan Hsiao i Yi-Shiuan Wu, 2004, Using Neural Network Theory to Predict the Properties of Melt Spun Fibers, Textile Research Journal Vol. 74, (09), s. 840-843.
13. Dlodlo N., Hunter L., Cele C., Metelerkamp R., Botha A.F., 2007, A Hybrid Expert Systems Architecture for Yarn Fault Diagnosis. Fibers & Textiles in Eastern Europe, April/June, Vol. 15, No 2 (61), s. 43-49.
14. Duckett K., Zapletalova T., Cheng L., Ghorashi H., Watson M. D., 1999, Color Grading of Cotton, Part II: Color grading with an Expert System and Neural Networks, Textile Research Journal Vol.69(12), s. 893-903.
15. Ertugrul S., Ucar N., 2000, Predicting Bursting Strength of Cotton Plain Knitted Fabrics Using Intelligent Techniques, Textile Research Journal Vol. 70, (10), s. 845-851.
16. Fan J., Newton E., Au R., 2001, Predicting Garment Drape with a Fuzzy-Neural Network, Textile Research Journal Vol. 71, (07), s. 605-608.
17. Gong R. H., Chen Y., 1999, Predicting the Performance of Fabrics in Garment Manufacturing with Artificial Neural Network, Textile Research Journal Vol. 69, (07), s. 477-483.
18. Gurumerthy B. R., 2007,Prediction of Fabric Compressive Properties Using Artificial Neural Networks, Autex Research Journal, Vol. 7, No 1, March, s. 19-31.
19. Huang C-C., Chen I-Cc., 2001, Neural-Fuzzy Classification for Fabric Defects, Textile Research Journal, Vol. 71, (07), t. 220-224.
20. Huang Ch. Ch., Yu W. H., 2001, Fuzzy Neural Network Approach to Classifying Dyeing Defects, Textile Research Journal Vol. 71, (02), s. 100-104.
21. Huang Ch. Ch., Chang K. T., 2001, Fuzzy Self- Organizing and Neural Network Control of Silver Linear Density in a Drawing Frame, Textile Research Journal Vol. 71, (11), s. 987-992.
22. Hui C. L., Lau T. W., Ng S. F., Chan K. C. C., 2004, Neural Network Prediction of Human Psychological Perceptions of Fabric Hand, Textile Research Journal Vol. 74, (05), s. 375-382.
23. I-Shou Tsae, Chung-Hua Lin, Jeng-Jong Lin, 1995, Applying an Artificial Neural Network to Pattern Recognition in Fabric Defects, Textile Research Journal Vol. 65, (03), s. 123-130.
24. Jackowska-Strumiłło L., Jackowski T., Chylewska B., Cyniak D., 1998a, Application of a Hybrid Neural Model for Determination of Selected Yarn Parameters, Fibers & Textiles in Eastern Europe 4(23).
25. Jackowska-Strumiłło L., Jackowski T., Cyniak D., Czekalski J., 2004, Neural Model of the Spinning Process for Predicting Selected Properties of Flax/Cotton Yarn Blends, Fibers & Textiles in Eastern Europe, No 4 (48), Vol. 12.
26. Jackowski T., Jackowska-Strumiłło L., Chylewska B., Cyniak D., 1998b, Zastosowanie sztucznych sieci neuronowych do wyznaczania nierównomierności masy przędzy rotorowej. Materiały z Konferencji Naukowej, IMTEX 98, Łódź.
27. Jeffrey Kuo i Ching-Jeng Lee, 2003, A Back-Propagation Neural Network for Recognizing Fabric Defects, Textile Research Journal –Vol. 73, (02), 8. 147-152.
28. Jeng-Jong Lin, 2003, A Genetic Algorithm for Searching Weaving Parameters for Woven Fabrics, Textile Research Journal Vol. 73, (02), s. 105-112.
29. Jeng-Jong Lin, Chung-Hua Lin, I-Shou Tsai, 1995, Applying Expert System and Fuzzy Logic to an Intelligent Diagnosis System for Fabric Inspection, Textile Research Journal, Vol. 65 (12), s. 697-709.
30. Jeong B. S., Bae J. H., Suh M. W., 2003, Automatic Recognition of Woven Fabric Patterns by an Artificial Neural Network, Textile Research Journal Vol. 73, (07), s. 645-650.
31. Kang T. J., Kim S., Ch., 2002, Objective Evaluation of the Trash and Color of Raw Cotton by Image Processing and Neural Network ,Textile Research Journal, Vol. 72, s. 776-782.
32. Kuo C-F. J, Liu C-H., 1999, Theoretical Control and Experimental Verification of Carded Web Density, Part II: Pole Placement Design Through State Feedback, Text. Res. J., 69, (4), s. 237-244.
33. Kuo C-F. J., Hsiao K-I, Wu Y-S., 2004b, Using Neural Network Theory to Predict the Properties of Melt Spun Fibers, Text. Res. J., 74, (9), s. 840-843.
34. Kuo C-F. J., Hsiao K-I, Wu Y-S., 2()04a, Using Fuzzy Theory to Predict the Properties of a Melt Spinning System, Text. Res. J., 74, (3), s. 231-236.
35. Kuo C-F. J., Lee C-J., Tsai C-C., 2003, Using a Neural Network to Identify Fabric Defects in Dynamic Cloth Inspection, Text. Res. J., 73, (3), s. 238-245.
36. Kuo C-F. J., Shih C-Y, Lee J-Y., 2004, Automatic Recognition of Fabric Weave Patterns by a Fuzzy C-Means Clustering Method, Text. Res. J., 74, (2), s. 107-112.
37. Kuo C-F. J., Wang C-C, Hsieh C-T., 1999, Theoretical Control and Experimental Verification of Carded Web Density, Part III: Neural Network Controller Design, Text. Res. J., 69, (5), s. 401-407.
38. Kuo C-F. J., Lec C-J., 2003, A Back-Propagation Neural Network for Recognizing Fabric Defects, Text. Res. J., 73, (2), s. 147-152.
39. Lewandowski S., 2008a, Podstawowe elementy sztucznej inteligencji i przykłady ich zastosowań we włókiennictwie, cz. Ia.: Rodzaje i charakterystyka elementów sztucznej inteligencji. Przegląd Włókienniczy - Włókno Odzież Skóra, 62, (4), s. 43-46.
40. Lewandowski S., 2008b, Podstawowe elementy sztucznej inteligencji i przykłady ich zastosowań we włókiennictwie, cz. Ib.: Rodzaje i charakterystyka elementów sztucznej inteligencji, Przegląd Włókienniczy - Włókno Odzież Skóra, 62, (5), s. 47-48.
41. Lewandowski S., 2008c, Podstawowe elementy sztucznej inteligencji i przykłady ich zastosowań we włókiennictwie, cz. Ic: Rodzaje i charakterystyka elementów sztucznej inteligencji, Przegląd Włókienniczy - Włókno Odzież Skóra, 62, (7), s. 33-35.
42. Lewandowski S., Drobina R., 2008a, Prediction of Properties of Unknotted Spliced Ends of Yarns Using Multiple Regression and Artificial Neural Networks, Part I: Identification of Spliced Joints of Combed Wool Yarn by Artificial Neural Networks and Multiple Regression, Fibers Text. East. Eur., 16, No 5 (70), s. 33-39.
43. Lewandowski S., Drobina R., 2008b, Prediction of Properties of Unknotted Spliced Ends of Yarns Using Multiple Regression and Artificial Neural Networks, Part II: Verification of Regression Models, Fibers Text. East. Eur., 16, No 6 (71), s. 20-27.
44. Lewandowski S., Stańczyk T., 2005, Identification and Classification of Spliced Wool Combed Yarn Joints by Artificial Neural Networks, Part II: Interpretation of identification and classification results of the unknotted spliced yarns joints, Eastern & Textiles in Eastern Europe Vol. 13, No 2(50), s 16-19.
45. Lewandowski S., Stańczyk T., 2005, Identification and Classification of Spliced Wool Combed Yarn Joints by Artificial Neural Networks, Part I: Developing an Artificial Neural Network Model, Eastern & Textiles in Eastern Europe Vol. 13.
46. Lieberman M. A., Patil R. B., 1994, Clustering and Neural Networks to Categorize Cotton Trash, Optic Eng 33, s. 1642-1653.
47. Lin J-J., 2003, A Genetic Algorithm for Searching Wearing Parameters for Woven Fabrics, Textile Research Journal Vol. 73, (02), s. 105-112.
48. Lin J-J., Lin C-H., Tsai I-S., 1995, Applying Expert System And Fuzzy Logic To An Intelligent Diagnosis System For Fabric Inspection. Textile Research Journal, Vol. 65 (12), s. 697-709.
49. Majumdar A., Majumdar P. K., Sarkar B., 2004, Selecting Cotton Bales by Spinning Consistency Index and Micronaire Using Artificial Neural Networks, Autex Research Journal, Vol. 4, No 1, March, s. 1-8.
50. Majumdar P. K., Majumdar A., 2004, Predicting the Breaking Elongation of Ring Spun Cotton Yarns Using Mathematical, Statistical, and Artificial Neural Network Models, Textile Research Journal Vol. 74, s. 652-655.
51. Mori T., Komiyama J., 2002, Evaluating Wrinkled Fabrics with Image Analysis and Neural Networks, Textile Research Journal Vol. 72, (05), s. 417-422.
52. Dlodlo N., Hunter L., Cele C., Metelerkamp R., Botha A. F., 2007, A Hybrid Expert Systems Architecture for Yarn Fault Diagnosis, Fibers & Textiles in Eastern Europe, April/June, Vol. 15, No 2 (61), s. 43-49.
53. Ogulata S. N., Sahin C., Ogulata R. T., Onur Balci., 2006, The Prediction of Elongation and Recovery of Woven Bi-Stretch Fabric Using Artificial Neural Network and Linear Regression Models, Fibers & Textiles in Eastern Europe. April/June, Vol. 14, No 2 (56). s. 46-49.
54. Park S. W., Hwang Y. G., Kang B. C, 2000, Applying Fuzzy Logic and Neural Networks to Total Hand Evaluation of Knitted Fabrics, Textile Research Journal Vol. 70, (08), s. 675-681.
55. Rabiej M., 2003, Application of the genetic algorithms and multi-objective optimization to the resolution of X-Ray diffraction curves of semicrystalline polymers, Fibers & Textiles in Eastern Europe January/December, Vo.11. No. 5 (44) s. 83-87. Röösli H.. 2000. The flexible blow room – the safe investment for the future. Rieter spinning systems.
56. Semnani D, Latifi M. A., Pourdeyhimi B., Merati A. A., 2006, Grading of Yarn Appearance Using Image Analysis and an Artificial Intelligence Technique, Textile Research Journal, Vol, 76 (03), s. 187-196.
57. Sette S., Boullart L., Kiekens P., 1995, Self-Organizing Neural Nets, A New Approach to Quality in Textiles, Textile Research Journal Vol. 65, (04), s. 196-202.
58. Sette S., Boullart L., Van Langenhove L., 2000. Building a Rule Set for the Fiber-to-Yarn Production Process by Means of Soft Computing Techniques, Textile Research Journal Vol. 70, (05), s. 375-386.
59. Sette S., Boullart L., Van Langenhove L., Kiekens P., 1997, Optimizing the Fiber-to-Yarn Production Process with a Combined Neural Network/Genetic Algorithm Approach, Textile Research Journal, Vol. 67 (02), s. 84-92.
60. Sette S., Van Langenhove L., 2003, The complex relationships between fibres, production parameters and spinning results, Department of Textiles Ghent University, Belgium.
61. She F. H., Kong L. X., Nahavandi S., Kouzani A. Z., 2002, Intelligent Animal Fiber Classification with Artificial Neural Networks, Textile Research Journal Vol. 72, (07), s. 594-600.
62. Shiau Y-R., Tsai I-S., Lin C-S., 2000, Classifying Web Defects with a Back-Propagation Neural Network by Colour Image Processing, Textile Research Journal Vol. 70, (07), s. 633-640.
63. Shyr T. W., Lai S. S., Lin J. Y., 2004, New Approaches to Establishing Translation Equations for the Total Hand Value of Fabric, Textile Research Journal Vol. 74, (06), s. 528-534.
64. Sung Hoon Jeong, Hyung Taek Choi, Sook Rae Kim, Jae Yun Jaung, Seong Hun Kim, 2001, Detecting Fabric Defects With Computer Vision And Fuzzy Rule Generation, Part II: Defect Identification by a Fuzzy Expert System, Textile Research Journal Vol. 71, (07), s. 563-573.
65. Tokarska M., 2006, Assessing the Quality of Neural Models Using a Model of Flow Characteristics of Fabrics as an Example, Autex Research Journal, Vol. 6, No 3, March, s. 162-168.
66. Tsae I-S, Lin C-H., Lin J-J., 1995, Applying an Artificial Neural Network to Pattern Recognition in Fabric Defects, Textile Research Journal Vol. 65, (03), s. 123-130. 67.
67. Uçar N., Ertugrul S., 2007, Prediction of Fuzz Fibers on Fabric Surface by Using Neural Network and Regression Analysis, April/June, Vol. 15, No 2(61), s. 58-61.
68. Wong A. S. W., Li Y., Yeung P. K. W., Lee P. W. H.,2003, Neural Network Predictions of Human Psychological Perceptions of Clothing Sensory Comfort, Textile Research Journal Vol. 73, (01), s. 31-36.
69. Wong A. S. W., Li Y., Yeung P. K. W., 2004, Predicting Clothing Sensory Comfort with Artificial Intelligence Hybrid Models, Textile Research Journal, Vol. 74, (01), s. 13-19.
70. Xu B., Su J., Dale D., S., Watson M. D„ 2000, Cotton Color Grading with a Neural Network, Textile Research Journal Vol. 70 (05), s. 430-436.
71. Xu B., Dale D. S., Huang Y., Watson M. D., 2002, Cotton Color (Classification by Fuzzy Logic, Textile Research Journal Vol. 72 (06), s. 504-509.
72. Yao G., Guo J., Zhou Y., Hua D., 2005, Predicting the Warp Breakage Rate in Weaving by Neural Network Techniques, Textile Research Journal (03), s. 274-278.
73. Yau-Ren Shiau, I-Shou Tsai, Chih-Shiang Lin, 2000, Classifying Web Defects with a Back-Propagation Neural Network by Colour Image Processing, Textile Research Journal Vol. 70, (07), s. 633-640.
74. Zeng Y. C., Wang K.F., Yu C.W., 2004, Predicting the Tensile Properties of Air-Jet Spun, Textile Research Journal Vol. 74, (08), s. 689-694.

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-article-BPS2-0052-0095