Open AccessOBTAINING TEXTILE WITH STRUCTURES AND FUNCTIONALITIES MODELED AND REFERENCED CLASSIFIED IN THE NONMARKOV NEURAL NETWORKS
Author(s) -
Ioan Gâf-Deac,
Emilia Visileanu,
Diana Păun,
Cristina Monica Valeca,
Viorel Streza
Publication year - 2019
Publication title -
tex teh
Language(s) - English
Resource type - Journals
ISSN - 2068-9101
DOI - 10.35530/tt.2019.39
Subject(s) - artificial neural network , flexibility (engineering) , computer science , textile , constant (computer programming) , point (geometry) , markov chain , artificial intelligence , mathematics , materials science , machine learning , geometry , composite material , statistics , programming language
In the paper the new original idea is launched that in fact the behavior of the fabric must be examined from the point of view of preserving the quasi-constant "fixed" behavior in the form, the use properties and the content of the use / consumption, respectively in order to ensure a networks of interspaces in the fabric which allow flexibility of the properties and characteristics required by the use. Based on this, systematized sources of evidence are obtained to obtain products with referenced structured and referenced structures and functionalities in non-Markov neural networks. As such, the "empty" spaces in textile fabrics with structures and functionalities modeled and referenced in non-Markovian neural networks are in fact only generically called so because there is an "absolute vacuum".