Development of a high-speed algoritm of neurological conclusion

Isamiddin Siddikov, D Yadgarova

Тошкент давлат техника университети хабарлари · 2019-yil

Annotatsiya

One of the ways to increase the efficiency of the process of managing continuous dynamic objects is to develop new or improve existing control systems based on modern methods involving the achievements of information technology. The article deals with the creation of highly efficient control algorithms for technological objects, operating in conditions of uncertainty, designed to manage real-life objects. An algorithm is proposed for the structural-parametric adaptation of the PID parameters (proportional-integral-differential) -regulator, which allows to reduce the number of iterations in the learning process of the fuzzy-logical inference algorithm by reducing empty solutions. To determine the empty solutions, hybrid algorithms are used, which include modernized genetic and immune algorithms, which in turn allow you to configure the adaptation parameters of artificial neural network models. A block diagram of an automated control system for executive mechanisms is proposed, which includes a block for adapting the correction of not only parameters, but also the structure of the control system, which allows to reduce the error in the results of training a neuro-fuzzy network from 8 to 1%. The proposed algorithm is simple to implement on microcontrollers, which allows it to be implemented in the tasks of process control in the conditions of information uncertainty in real conditions at the operation stage.

Maqola ma’lumotlari
MualliflarIsamiddin Siddikov, D Yadgarova
JurnalТошкент давлат техника университети хабарлари
NashriyotТошкент давлат техника университети
ISSN2181-0400, 2181-1180
Nashr sanasi2019-06-11
Jild2019
Son1
Betlar154-160
TilIngliz
Ilmiy sohaTexnika
DOI10.51346/tstu-01.19.1.-77-0014
Indeksga qo‘shilgan2026-09-02

DOI: 10.51346/tstu-01.19.1.-77-0014 · Maqolaning asl sahifasi

Ilmiy soha

Texnika

Iqtibos keltirish

APAIsamiddin Siddikov, & D Yadgarova (2019). DEVELOPMENT OF A HIGH-SPEED ALGORITM OF NEUROLOGICAL CONCLUSION. Тошкент давлат техника университети хабарлари, 2019(1), 154-160. https://doi.org/10.51346/tstu-01.19.1.-77-0014
GOST (OAK)Isamiddin Siddikov, D Yadgarova DEVELOPMENT OF A HIGH-SPEED ALGORITM OF NEUROLOGICAL CONCLUSION // Тошкент давлат техника университети хабарлари. – 2019. – T. 2019, № 1. – P. 154-160. – DOI: 10.51346/tstu-01.19.1.-77-0014.
MLAIsamiddin Siddikov, and D Yadgarova. “DEVELOPMENT OF A HIGH-SPEED ALGORITM OF NEUROLOGICAL CONCLUSION.” Тошкент давлат техника университети хабарлари, 2019(1), 154-160, 2019. https://doi.org/10.51346/tstu-01.19.1.-77-0014
ChicagoIsamiddin Siddikov, and D Yadgarova. “DEVELOPMENT OF A HIGH-SPEED ALGORITM OF NEUROLOGICAL CONCLUSION.” Тошкент давлат техника университети хабарлари, 2019(1), 154-160 (2019). https://doi.org/10.51346/tstu-01.19.1.-77-0014
HarvardIsamiddin Siddikov, and D Yadgarova (2019) ‘DEVELOPMENT OF A HIGH-SPEED ALGORITM OF NEUROLOGICAL CONCLUSION’, Тошкент давлат техника университети хабарлари, 2019(1), 154-160. https://doi.org/10.51346/tstu-01.19.1.-77-0014
BibTeX
@article{isamiddinsiddikov2019,
  title = {DEVELOPMENT OF A HIGH-SPEED ALGORITM OF NEUROLOGICAL CONCLUSION},
  author = {Isamiddin Siddikov and D Yadgarova},
  journal = {Тошкент давлат техника университети хабарлари},
  year = {2019},
  volume = {2019},
  number = {1},
  pages = {154-160},
  doi = {10.51346/tstu-01.19.1.-77-0014},
  url = {https://doi.org/10.51346/tstu-01.19.1.-77-0014}
}

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