NEURO-FUZZY MODELING OF EXPERIMENTAL DATA ON OPTIMIZATION OF THE SPECTRAL CHARACTERISTICS OF FOCL

Authors

  • Dilmurod Davronbekov Tashkent University of Information Technologies named after Muhammad al-Khwarizmi
  • Zafar Khakimov Center for Higher Education Development Research and Introduction of Advanced Technologies
  • Jamshid isroilov

Keywords:

approximation, regression model, Sugeno fuzzy knowledge base, neuro-fuzzy model, spectral line, FOCL, FOTS

Abstract

In this article, we consider the issues of approximating experimental data. It is shown that
the advantage of using fuzzy methods in comparison with other existing methods when choosing an
approximation model is efficiency in solving non-formalized or poorly formalized problems, efficiency
when working with a large amount of conflicting information, efficiency when working with incomplete
information. The approximation of experimental data on the study of spectral lines of FOCL using
the regression model, the Sugeno fuzzy knowledge base and the neuro-fuzzy model is carried out.

Published

2021-03-26

How to Cite

Davronbekov, D., Khakimov, Z., & isroilov, J. (2021). NEURO-FUZZY MODELING OF EXPERIMENTAL DATA ON OPTIMIZATION OF THE SPECTRAL CHARACTERISTICS OF FOCL. Acta of Turin Polytechnic University in Tashkent, 11(1). Retrieved from http://acta.polito.uz/index.php/journal/article/view/4