In 2022, 28 important scientific results were obtained on the research work performed at the Institute, 7 of which were approved by the Science Council.
1. Algorithms for calculating the estimates of highorder statistical noise characteristics were developed. A matrix of highorder moments of noise at different moments of time was compiled. To validate the reliability of the developed algorithms, a software package was created and computational experiments were conducted.
Implemented by: Academician Telman Aliev, Prof. Naila Musaeva, Doctor of Engineering
Results published as:
1. Telman Aliev, Naila Musaeva. Technologies for monitoring the technical condition of transport infrastructure objects based on the coefficient of correlation between critical values of noise and useful signals // Transport Problems, 2022, vol.17, Issue 2, pp. 213224 (WoS – 0,13, SJR 0,304)
2. Telman Aliev, Naila Musaeva, Tofig Babayev, Ana Mammadova, Elnur Alibayli. Technologies And Intelligent Systems For Adaptive Vibration Control In Rail Transport// Transport Problems, 2022, Vol.17, issue 3, pp.3138 (WoS – 0,13, SJR 0,304)
3. Telman Aliev, Tofig Babayev, Rauf Gadimov, Narmin Rzayeva. Intellectualization of Vibration Control of Malfunctions in Rail Transport // XIV International Scientific Conference “Transport Problems”, Poland, University of Technology Faculty of Transport and Aviation Engineering Katowice – Silesia, 29 June – 1 July 2022
2. A methodology was proposed for modeling abruptly changing modes that disrupt the operation of economic, ecological, sociological, biological, etc. systems in a wide range and cause instability.
Implemented by: Corresponding Member of ANAS Aminaga Sadigov
Results published as:
1. A.B. Sadigov, İ.İ. Mustafayev. Modeling of Regimes with Sudden Change. “Reliability: Theory and Applications”, Special Issue, USA, 2022, № 4 (70), Vol.17, pp. 111117 (SJR 0,14)
2. A.B. Sadigov, İ.İ. Mustafayev. Modeling of Regimes with Sudden Change. Proseedings of 4th Eurasian Conference and Symposium RISK2022 “Innovations in Minimization of Natural and Technological Risks”, Baku, October 1113, 2022, 23 s.
3. A.B. Sadigov, B.H. Salayev, S.S. Gezalov. Modeling of Human Actions and Psychophysical Reactions in Emergency Situations. Informatics and Control Problems, 2022, 42 Issue 1, pp. 310.
4. Aminagha Sadigov, Sayavush Gezalov. Modeling of Actions and Psychophysical Processes in Emergencies. Proceedings of International Scientific Conference "Science, technology and innovative technologies". June 1213, 2022, Ashgabat, pp. 7274
3. New replenishment strategies in queue inventory systems, whose inventory can be replenished from various sources, were proposed, mathematical models of the considered systems when using these strategies were built, their ergodicity conditions were found, and effective numerical methods for calculating and optimizing their characteristics were created.
Implemented by: Corresponding Member of ANAS Agasi Melikov
Results published as:
1. Melikov A., Shahmaliyev M. Markovian models of queuing systems with positive and negative // Communications in Computer & Information Science. Springer. 2022. Vol. 1605. P. 2839 (SJR – 0,209)
2. A.Melikov, M.Shahmaliyev, J.Sztrik. Matrixgeometric solutions for the models of perishable inventory systems with a constant retrial rate // Communications in Computer & Information Science. Springer. 2022. Vol. 1552. P. 163173 (SJR – 0,209)
3. А.З.Меликов, Э.В.Мехбалыева. Системы обслуживания с гетерогенными серверами и зависящими от состояния скачкообразными приоритетами // Вестник Томского Государственного Университета. Управление, вычислительная техника, информатика. 2022. № 58. С. 8296. (WoS və SJR)
4. Melikov A., Mirzayev R., Nair S. Numerical investigation of double source queuinginventory systems with destructive customers // Journal of Computer and Systems Sciences International. 2022. Vol. 61. Issue 4. P. 581598 (WoS – 0,722)
5. Melikov A., Aliyeva S., Nair S., Krishna Kumar B. Retrial queuinginventory systems with delayed feedback and instantaneous damaging of items // Axioms. 2022. Vol. 11. Issue 5. Article 241. 17 pages (WoS – 1,824)
6. Melikov A., Mirzayev R., Nair S. Double Sources QueuingInventory System with Hybrid Replenishment Policy // Mathematics, 2002. 10(14). Article 2423. 16 pages (WoS – 1,824)
7. Melikov A., Krishnamoorthy A., Shajin D., Sztrik J. Multiserver queuing production inventory system with emergency replenishment // Mathematics. 2002. 10. Article 3839. 25 pages (WoS – 2,592)
8. Меликов А.З., Мирзоев Р.Р., Наир С. Метод расчета характеристик системы обслуживания c гибридной политикой пополнения запасов от двух источников // Distributed Computer and Communication Networks (DCCN2022). Proceeding of the XXV International Scientific Conference. Moscow. September 2630, 2022. P. 143149.
4. An approach to building feedback control systems using both current and previous information about the state of the controlled process was developed. Necessary optimality conditions for the synthesized feedback parameters were obtained, numerical schemes using the obtained conditions to solve the problems were developed. Computer experiments were conducted to solve the test problems.
Implemented by: Corresponding Member of ANAS Kamil Aydazade, Prof. Vagif Abdullayev, Doctor of Mathematics, Assoc. Prof. Samir Guliyev, Doctor of Mathematics
Results published as:
1. Aidazade K.R., Abdullayev V.M. “Controlling the heating of a rod using the current and preceding time feedback”, Autom. Remote Control, 2022, 83:1, 106–122 (WoS  0,538)
2. Айдазад К.Р., Абдуллаев В.М. “Управление процессом нагрева стержня с использованием текущей и предыдущей по времени обратной связи”, Автомат. и телемех., 2022, 1, с.130149 (РИНЦ)
3. K.R.Aidazade, V.M.Abdullayev “Rod temperature regulation using current and timedelayed feedback”, Quaestiones Mathematicae, 2022, 45 (8), 22 p. (WoS  0.81, Q3)
4. Guliyev S.Z. “Synthesis of zonal controls for a problem of heating with delay under nonseparated boundary conditions”, Cybernetics and Systems Analysis, Springer, 2018. v.54, p.110121. (WoS – 0,15, SJR – 0,382)
5. A class of inverse source problems for a parabolic equation with nonlocal initial and boundary conditions was investigated. The peculiarity of the class of problems is that the recovered parameters depend only on the time or space variable. To solve the considered problems, an iterative numerical method based on the straight line method and a special indication of the solution of the obtained auxiliary boundary problems was proposed. The software was developed. Computer experiments on the test problems were conducted.
Implemented by: Corresponding Member of ANAS Kamil Aydazade, Assoc. Prof. Anar Rahimov, Doctor of Mathematics
Results published as:
1. Aidazade K.R., Rahimov A.B. On recovering space or timedependent source functions for a parabolic equation with nonlocal conditions // Applied Mathematics and Computation, Elsevier Inc., 2022. v. 419, No 8, 126849 (17 pages). (WoS 4,397, Q1)
2. Aidazade K.R., Rahimov A.B. Numerical Solution to Inverse Problems of Recovering SpecialType Source of a Parabolic Equation. In: Mathematical Analysis in Interdisciplinary Research. Springer Optimization and Its Applications, Parasidis I.N. et.al. (eds.), Springer, Cham, 2021, online first 2022, Vol. 179, pp. 85100 (Scopus)
3. Aidazade K.R., Rahimov A.B. On problem of restoring space coeffıcientfunctions of special type source in parabolic equation // Proceedings of the 8th International Conference on Control and Optimization with Industrial Applications (COIA2022), 2426 August, 2022, vol. 2, pp. 4547. (WoS)
6. The optimal Bolza control problem specified by higherorder and phaselimited differential inclusions was investigated. Adequate optimality conditions were obtained using the additive differential Mahmudov inclusion, which is a generalization of EulerLagrange inclusions and transversality conditions, as well as the classical EulerPoisson equation of the theory of calculus of variations. The results obtained may find a variety of practical applications in solving the problems of economic process control, in particular, the described polyhedral differential inputs in the framework of the wellknown NeumannGale economic model.
Implemented by: Prof. Elimkhan Mahmudov, Doctor of Mathematics
Results published as:
1. E.Mahmudov. Optimization of the Bolza problem with higherorder differential inclusions and initial point and state constraints, journal of Nonlinear and Convex Analysis, 2022, vol. 23, No 5, pp. 917941. (WoS 1,016, Q2)
2. E.Mahmudov. Optimization of Firstorder Nicoletti BoundaryValue Problem with Discrete and Differential Inclusions and Duality, Optimization, 2022. (WoS  2,456, Q1)
3. E.N.Mahmudov. Optimal Control of the Generalized Rockafellar Problem, The 8th International Conference on Control and Optimization with Industrial Applications (COIA 2022) 2426 August, 2022, Baku (WoS)
7. For joint investigation of problems of classification of user queries, construction of the language model and identification of names of beings in the dialogue systems in the Azerbaijani language, the model of neural network based on the transformer was developed. The objective function used for training of the proposed neural network was minimized as a convolution of the objective functions of the above problems. The paper shows that the neural network built in this way gives more satisfactory results in this area, because it simultaneously studies the language model describing the domain of application, along with the identification of the user query.
Implemented by: Assoc.Prof. Samir Rustamov, PhD in Engineering
Results published as:
1. S.Rustamov, A.Bayramova, E.Alasgarov “Development of dialogue management system for banking services”, Applied Sciences, 2021, N11(22) (WoS  2.679, Q2)
2. A. Valizada, N. Akhundova, and S. Rustamov, “Development of speech recognition systems in emergency call centers,” Symmetry, apr. 2021, vol. 13, no. 4, p. 634. (WoS – 2,645)
3. A. Valizada, S. Jafarova, E. Sultanov, and S. Rustamov, “Development and evaluation of speech synthesis system based on deep learning models,” Symmetry, may 2021, vol. 13, no. 5, p. 819. (WoS – 2,645).
4. Y.Maksum, A.Amirli, A.Amangeldi, M.Inkarbekov, Y.Ding, A.Romagnoli, S.Rustamov, B.Akhmetov “Computational Acceleration of Topology Optimization Using Parallel Computing and Machine Learning Methods”, Journal of Industrial Information Integration, 2022, vol. 28, №7, 100352 (35 pages) (WoS  11,718, Q1, SJR2,745)

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