Data Processing System for NonStationary Processes Based on The Synthesis of Soft Computing Components

Authors

  • Kholmonov Sunatillo Makhmudovich PhD in Technical Sciences, Department of Information Technologies, Samarkand State University, Samarkand, Uzbekistan
  • Mirsanova Gulbahor Muhammadi qizi Graduate student, Department of Information Technologies, Samarkand State University, Samarkand, Uzbekistan

Keywords:

Non-Stationary Process, Processing, Neural Network, Fuzzy Set, Fuzzy Inference

Abstract

The problem has been formulated and the scientific and methodological foundations of data processing systems for non-stationary objects based on neural networks, fuzzy set models, fuzzy inference algorithms, and neuro-fuzzy networks have been developed. Are proposed mechanisms for structural and parametric identification, finding a set of terms of linguistic variables, rules of inference, determining the coefficients of fuzzy rules, using the properties of self-adaptation, self-regulation, network organization, and the formation of databases and knowledge. The efficiency of the implemented algorithms was evaluated on the basis of test unimodal and multimodal output functions.

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Published

2022-03-14

Issue

Vol. 4 (2022): EJET

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

Data Processing System for NonStationary Processes Based on The Synthesis of Soft Computing Components. (2022). Eurasian Journal of Engineering and Technology, 4, 26-31. https://geniusjournals.org/index.php/ejet/article/view/757