Introduction Artificial Neuron Networks
Keywords:
artificial neural network, training, weight coefficients, input layer, latent layer, output layer
Abstract
Nowadays, a wide range of new possibilities for the construction of intelligent systems for the control of technological processes are developing through the use of artificial neural networks. The article describes the widespread use of symbols through artificial neural networks in issues such as recognition, prediction and diagnosis, optimization, signal processing under the influence of noise, and discusses the main parameters of the artificial neural network by the authors.
References
1. Michael T., McGrath, Cliodhna Ni Scanaill. Sensor Technologies. Apress Media. LCC, New York (NY). USA, 2014. – 321 p
2. N.R.Yusupbekov, R.A.Aliev, R.R.Aliev, A.N.Yusupbekov, Intellektual'ny'e sistemy' upravleniya i prinyatiya resheniy [Intelligent management and decision-making systems]. Tashkent: Uzbek-skaya nacional'naya e`nciklopediya, 2014, 490 p.
3. Uljaev E., Narzullayev S., Utkir U., Shoira S. (2022) Increasing the Accuracy of Calibration Device for Measuring the Moisture of Bulk Materials. In: Cioboată D.D. (eds) International Conference on Reliable Systems Engineering (ICoRSE) - 2021. ICoRSE 2021. Lecture Notes in Networks and Systems, vol 305. Springer, Cham. https://doi.org/10.1007/978-3-030-83368-8_20.
4. M. A. Nielsen, Neural networks and deep learning. Determination Press, 2015.
5. Uljaev E., Narzullayev Sh.N., Artificial neural networks for measuring the moisture of bulk materials // Chemical Technology, Control and Management. 2021. Vol. 2021: Iss. 4, Article 4, – pp. 24-31, https://doi.org/10.51346/tstu-02.21.4-77-0027.
6. Uljayev E., Ubaydullayev U.M., Tadjitdinov G.T., Narzullayev S. (2021) Development of Criteria for Synthesis of the Optimal Structure of Monitoring and Control Systems. In: Aliev R.A., Yusupbekov N.R., Kacprzyk J., Pedrycz W., Sadikoglu F.M. (eds) 11th World Conference “Intelligent System for Industrial Automation” (WCIS-2020). WCIS 2020. Advances in Intelligent Systems and Computing, vol 1323. Springer, Cham. https://doi.org/10.1007/978-3-030-68004-6_73E.
7. А.V.Gavrilov, Gibridnye intellektual'nye sistemy [Hybrid intelligent systems]. Novosibirsk: Izd-vo NGTU, 2003, 164 p. (in Russian).
8. А.R.Marakhimov, Kh.Z.Igamberdiev, А.N.Yusupbekov, I.Kh.Siddikov, Nechetko-mnozhestvennye modeli i intellektual'noe upravlenie tekhnologicheskimi protsessami [Fuzzy-set models and intelligent process control]. Tashkent: TashGTU, 2014, 240 p.
2. N.R.Yusupbekov, R.A.Aliev, R.R.Aliev, A.N.Yusupbekov, Intellektual'ny'e sistemy' upravleniya i prinyatiya resheniy [Intelligent management and decision-making systems]. Tashkent: Uzbek-skaya nacional'naya e`nciklopediya, 2014, 490 p.
3. Uljaev E., Narzullayev S., Utkir U., Shoira S. (2022) Increasing the Accuracy of Calibration Device for Measuring the Moisture of Bulk Materials. In: Cioboată D.D. (eds) International Conference on Reliable Systems Engineering (ICoRSE) - 2021. ICoRSE 2021. Lecture Notes in Networks and Systems, vol 305. Springer, Cham. https://doi.org/10.1007/978-3-030-83368-8_20.
4. M. A. Nielsen, Neural networks and deep learning. Determination Press, 2015.
5. Uljaev E., Narzullayev Sh.N., Artificial neural networks for measuring the moisture of bulk materials // Chemical Technology, Control and Management. 2021. Vol. 2021: Iss. 4, Article 4, – pp. 24-31, https://doi.org/10.51346/tstu-02.21.4-77-0027.
6. Uljayev E., Ubaydullayev U.M., Tadjitdinov G.T., Narzullayev S. (2021) Development of Criteria for Synthesis of the Optimal Structure of Monitoring and Control Systems. In: Aliev R.A., Yusupbekov N.R., Kacprzyk J., Pedrycz W., Sadikoglu F.M. (eds) 11th World Conference “Intelligent System for Industrial Automation” (WCIS-2020). WCIS 2020. Advances in Intelligent Systems and Computing, vol 1323. Springer, Cham. https://doi.org/10.1007/978-3-030-68004-6_73E.
7. А.V.Gavrilov, Gibridnye intellektual'nye sistemy [Hybrid intelligent systems]. Novosibirsk: Izd-vo NGTU, 2003, 164 p. (in Russian).
8. А.R.Marakhimov, Kh.Z.Igamberdiev, А.N.Yusupbekov, I.Kh.Siddikov, Nechetko-mnozhestvennye modeli i intellektual'noe upravlenie tekhnologicheskimi protsessami [Fuzzy-set models and intelligent process control]. Tashkent: TashGTU, 2014, 240 p.
Published
2022-06-30
How to Cite
[1]
Uljaev, E., Sapayev, M., Narzullayev, S.N., Xudoyberdiyev, E.F. and Sodiqova, F.B. 2022. Introduction Artificial Neuron Networks. International Journal on Integrated Education. 5, 6 (Jun. 2022), 589-593. DOI:https://doi.org/10.17605/ijie.v5i6.3312.
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