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

Fibres and Textiles in Eastern Europe

Volumn 13, Issue 2, 2005, Pages 16-19

  Lewandowski, Stanisław ^a   Stańczyk, Tomasz ^a  

^a UNIVERSITY OF BIELSKO BIALA   (Poland)

Author keywords

Artificial neural network; Joint classification; Learning error; Spliced yarn joint; Winner neuron; Wool combed yarn; Yarn identification

Indexed keywords

TEXTILE INDUSTRY; WOOL; YARN;

ARTIFICIAL NEURAL NETWORK MODELING; CLASSIFICATION RESULTS; CONSTRUCTED NETWORKS; JOINT CLASSIFICATION; LEARNING ERROR; SPLICED YARN JOINT; WINNER NEURON; WOOL COMBED YARN; YARN IDENTIFICATION;

NEURAL NETWORKS;

CLASSIFICATION;

EID: 22944492070     PISSN: 12303666     EISSN: 23007354     Source Type: Journal    
DOI: None     Document Type: Article

References (6)

1. Servicing instruction of Jointair 4941 Splicer, Mesdan firm.
2. Servicing instruction of Espero automatic winder, Savio firm.
3. M. Machnio, R. Drobina, T. Zuśka, Assessment of strength parameters of pneumatically spliced yams ends after breakage. Research report, University of Bielsko-Biala, 2003.
4. S. Lewandowski, R. Drobina, M. Walentak, Optimisation of splicing device with the aspect of joint appearance. Research report, University of Bielsko-Biala, 2003.
5. Sette S., Boullart L., Van Langenhove L. 'Building a Rule Set for the Fiber-to-Yarn Production Process by Means of Soft Computing Techniques', Textile Res. J. Vol. 70, (05/2000), pp. 375-386
6. Sette S., Boullart L., Van Langenhove L. 'The complex relationships between fibres, production parameters and spinning results', Department of Textiles Ghent University, Belgium, lieva.vanlangenhoveρug.ac.be