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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
combed wool yarn pneumatically spliced joints additive quantities
2009/6/15
Applying the software environment Statistica for neural networks allowed the use of artificial
neural networks and regression analysis to predict the physical properties of unknotted
joints of yarn ...
Shape Optimisation and Shape Identification for Transient Diffusion Problems in Textile Structures
diffusion textile structures sensitivity analysis shape optimisation
2009/2/13
The equation of substance balance and the set of boundary and initial conditions determine the transient diffusion problem within the homogenized textile structure. Introducing an arbitrary behavioral...
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 Yarn Joints
spliced yarn joint wool combed yarn yarn identification joint classification
2009/2/8
In the first part of the article an Artificial Neural Network (ANN) model designed to recognise and classify pneumatically spliced yarn joints was presented. The effectiveness of recognition and class...
Identification and Classification of Spliced Wool Combed Yarn Joints by Artificial Neural Networks. Part I: Developing an Artificial Neural Network Model
spliced yarn joints wool combed yarn yarn identification joint classification
2009/2/8
A new artificial neural network (ANN) has been created, similar to the ADALINE-type network,
with linear activation function and bubble error sorting, designed to recognise and classify pneumatically...