INCREASING THE CREDIBILITY OF TEXTS BASED ON NEURO-FUZZY NETWORKS WITH GENETIC OPERATORS FOR REGULATING VARIABLES

Authors

  • Kholmonov Sunatillo Makhmudovich PhD in Technical Sciences, Department of Information Technologies, Samarkand State University, Samarkand, Uzbekistan
  • Nomozov Abror Ismoilovich Graduate Student, Department of Information Technologies, Samarkand State University, Samarkand, Uzbekistan

DOI:

https://doi.org/10.17605/OSF.IO/EPTWM

Keywords:

electronic document, texts, reliability of information

Abstract

Tools for solving problems of recognition, classification, decision-making, mechanisms for increasing the reliability of texts of electronic documents in automated document management systems based on the implementation of neural networks, neuro-fuzzy networks, and genetic algorithms have been developed. The developed software-algorithmic complex for increasing the reliability of information and processing spatio-temporal data of dynamic documents generates, analyzes, tracks, tests, detects errors in texts and other anomalies. Technical and technological support is focused on the centralized placement of electronic documents and their use in distributed computing environments.

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Published

2022-03-11

How to Cite

Kholmonov Sunatillo Makhmudovich, & Nomozov Abror Ismoilovich. (2022). INCREASING THE CREDIBILITY OF TEXTS BASED ON NEURO-FUZZY NETWORKS WITH GENETIC OPERATORS FOR REGULATING VARIABLES. Innovative Technologica: Methodical Research Journal, 3(03), 20–27. https://doi.org/10.17605/OSF.IO/EPTWM

Issue

Vol. 3 No. 03 (2022): it.academiascience

Section

Articles