Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4101
Title: Statistical and computational intelligence tools for the analyses of warp tension in different back-rest oscillations
Authors: Turhan, Yıldıray.
Tokat, Sezai.
Eren, R.
Keywords: Back-rest oscillation
Cross-validation
Data regression
Neural networks
Radial basis function
Warp tension
Weft density
Fabrics
Mathematical models
Parallel processing systems
Quadratic programming
Radial basis function networks
Regression analysis
Stiffness
Weaving
Back-rest oscillations
Cross-validation technique
Multiple-regression models
Weft densities
Abstract: In this paper, experimental, computational intelligence based and statistical investigations of warp tensions in different back-rest oscillations are presented. Firstly, in the experimental stage, springs having different stiffnesses are used to obtain different back-rest oscillations. For each spring, fabrics are woven in different weft densities and the warp tensions are measured and saved during weaving process. Secondly, in the statistical investigation, the experimental data are analyzed by using linear multiple and quadratic multiple-regression models. Later, in the computational intelligence based investigation, the data obtained from the experimental study are analyzed by using artificial neural networks that are universal approximators which provide a massively parallel processing and decentralized computing. Specially, radial basis function neural network structure is chosen. In this structure, cross-validation technique is used in order to determine the number of radial basis functions. Finally, the results of regression analysis, the computational intelligence based analysis and experimental measurements are compared by using the coefficient of determination. From the results, it is shown that the computational intelligence based analysis indicates a better agreement with the experimental measurement than the statistical analysis. © 2007 Elsevier Inc. All rights reserved.
URI: https://hdl.handle.net/11499/4101
https://doi.org/10.1016/j.ins.2007.06.029
ISSN: 0020-0255
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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