310-316The application of adaptive neuro-fuzzy inference system for the prediction of strength transfer efficiencies of warp and weft yarns in woven fabrics has been studied. The developed neuro-fuzzy models are based on the input-output data sets of 264 woven fabric samples, out of which the data of 234 samples are used for developing the prediction models while data of 30 samples are used for models’ validation. The developed models are capable of predicting the warp and weft yarns strength transfer efficiencies quite accurately, given the strength of constituent yarns, the fabric count and the float length
An Elman network model was trained using Fletcher-Reeves Update training algorithm, and used to pred...
Yarn tenacity is one of the most important properties in yarn production. This paper addresses model...
In this study, an Artificia Neural Network (ANN) and a statistical model were developed to predict t...
19-25The breaking elongation of rotor-spun yarns has been predicted by using linear regression, art...
The main objective of this research is to predict the mechanical properties of viscose/lycra plain k...
Ultraviolet protection factor (UPF) of woven fabrics is modeled by using two soft computing approach...
The count-strength-product (CSP) of cotton yarn is a complex function of fiber properties and spinni...
Publisher Copyright: Copyright © 2021 by ASTM International.Micro plastic particles are a burgeoning...
2nd International Conference on Agents and Artificial Intelligence, ICAART 2010 -- 22 January 2010 t...
Abstract: In this study, the effects of yarn parameters, on the bursting strength of the plain knitt...
31-38This study aims at developing a new approach to predict and determine the quality of rotor-spun...
Stretch woven fabrics are widely used because of their good elongation and recovery (residual extens...
With the huge amounts of plastic bottles being consumed and disposed daily, people have been using d...
This paper investigates the use of extended normalized radial basis function (ENRBF) neural networks...
Predicting the tensile strength of polyester/viscose blended open-end rotor spun yarns using the art...
An Elman network model was trained using Fletcher-Reeves Update training algorithm, and used to pred...
Yarn tenacity is one of the most important properties in yarn production. This paper addresses model...
In this study, an Artificia Neural Network (ANN) and a statistical model were developed to predict t...
19-25The breaking elongation of rotor-spun yarns has been predicted by using linear regression, art...
The main objective of this research is to predict the mechanical properties of viscose/lycra plain k...
Ultraviolet protection factor (UPF) of woven fabrics is modeled by using two soft computing approach...
The count-strength-product (CSP) of cotton yarn is a complex function of fiber properties and spinni...
Publisher Copyright: Copyright © 2021 by ASTM International.Micro plastic particles are a burgeoning...
2nd International Conference on Agents and Artificial Intelligence, ICAART 2010 -- 22 January 2010 t...
Abstract: In this study, the effects of yarn parameters, on the bursting strength of the plain knitt...
31-38This study aims at developing a new approach to predict and determine the quality of rotor-spun...
Stretch woven fabrics are widely used because of their good elongation and recovery (residual extens...
With the huge amounts of plastic bottles being consumed and disposed daily, people have been using d...
This paper investigates the use of extended normalized radial basis function (ENRBF) neural networks...
Predicting the tensile strength of polyester/viscose blended open-end rotor spun yarns using the art...
An Elman network model was trained using Fletcher-Reeves Update training algorithm, and used to pred...
Yarn tenacity is one of the most important properties in yarn production. This paper addresses model...
In this study, an Artificia Neural Network (ANN) and a statistical model were developed to predict t...