Distributed Information Processing Systems Laboratory
The laboratory was organized in 1960 as a laboratory of "Telecommunication Systems" on the basis of the Institute of Automation.
Heads of the laboratory:
- PhD. Kurotchenko V.I. (1960 - 1984)
- PhD. Zamay V.I. (1985 - 2017)
- d.t. Lychenko N.M. (2018 - 2024)
- Since 2025, the laboratory is headed by Verzunov S.N.
Contacts
Verzunov Sergey Nikolayevich
Head of Laboratory, Doctor of Technical Sciences, Associate Professor
Address: 265 Chuy Avenue, Room 324, Bishkek 720071, Kyrgyz Republic
Tel.: +(996 553) 72-20-30
Email: verzunov@hotmail.com
Sectional navigation
Main Research Areas
- Development of information and telecommunication technologies for monitoring emergency geo-ecological situations.
- Development of effective technologies for forecasting environmental parameters.
Key results and achievements
Systems of telemechanization of irrigation facilities, automated water distribution management systems (ASUTP-V), information and control systems for water intake, warning systems for catastrophic floods, AFM POS with microservice architecture, forecasting of dangerous processes using neural network technologies have been developed.
The laboratory has more than 100 copyright certificates and patents, was awarded the State Prize of the Kyrgyz Republic, and developments were exhibited at international and national exhibitions.
Composition of the laboratory
Verzunov Sergey Nikolaevich
Head of the Distributed Information Processing Systems Laboratory, Doctor of Technical Sciences, Associate Professor
Lychenko Natalya Mikhailovna
Chief Researcher, Distributed Information Processing Systems Laboratory, Doctor of Technical Sciences, Professor
Velikanova Lyudmila Ivanovna
Senior Researcher, Distributed Information Processing Systems Laboratory
Gaydamako Valentina Viktorovna
Senior Researcher, Distributed Information Processing Systems Laboratory
Abubakerova Zulfiya Malikovna
Lead Engineer, Distributed Information Processing Systems Laboratory
Kazantsev Mikhail Romanovich
Engineer, Distributed Information Processing Systems Laboratory
Publications
Publications of 2016-2020 on air quality forecasting, virtualization of sensor devices, modeling of cloud systems, application of LSTM and neural network technologies are given.
List of publications
Publications 2020
Lychenko N.M., Sorokova A.V. Application of LSTM Neural Networks to Classify Air Quality Index Bishkek // Problems of automation and control. Bishkek: Ilim, 2020, No. 1 (38). C. 70-80. DOI: 10.5281/zenodo.3904130 Aveltsov D.O., Gaydamako V.V. Development of a module for virtualization of sensor devices for distributed information and measurement systems // Problems of automation and control. Bishkek: Ilim, 2020, No. 1 (38). 89-103. DOI: 10.5281/zenodo.3904148 Lychenko N.M., Sorokova A.V. Forecast of the air quality index as a classification problem depending on meteorological factors // Mathematical and computer modeling: a collection of materials of the VIII International Scientific Conference. Omsk, 2020. Gaydamako V.V. Application of real-time calculus to assess the performance of cloud services on the example of a three-level web application // Mathematical and computer modeling: a collection of materials of the VIII International Scientific Conference. Omsk, 2020. Lychenko N.M., Velikanova L.I., Verzunov S.N., Sorokova A.V. Models of forecasting the level of air pollution g. Bishkek // Bulletin of KRSU, 2020. Tom 20. - No. 12. Gaydamako V.V. Comparative analysis of analytical modeling methods for assessing the performance of cloud applications // KRSU Bulletin, 2020. Tom 20. - No. 12. Gaydamako V.V. Modeling the performance of a multi-level web application based on real-time calculation // Problems of automation and control. Bishkek: Ilim, 2020, No. 2 (39).Publications 2019
Verzunov S.N., Lychenko N.M. Comparative analysis of the capabilities of a multiwavelength neural network model for solving forecasting problems // KRSU Bulletin, 2019. Vol 19.-No4.S.39-45. https://elibrary.ru/download/elibrary_38171888_48590524.pdf Verzunov S.N., Lychenko N.M. Analysis and ARIMA-models of dynamics of PM2.5 concentration change in ambient air // Problems of automation and control. Bishkek: Ilim, 2019. N1(36). 21-30. Verzunov S.N., Lychenko N.M. Short-term forecasting of the air quality index based on ARIMA models // Mathematical and computer modeling: a collection of materials of the VII International Scientific Conference dedicated to the memory of S.S. Efimova. Omsk, 2019. 76-78. Velikanova L.I., Lychenko N.M. Multi-regression and generalized-regression neural network models of short-term forecast of PM2.5 pollution in the city. Bishkek taking into account meteorological parameters // Problems of automation and control. - Bishkek: Ilim, 2019. N2(37). 42-51. Lychenko N.M. Regression analysis of meteorological factors and particle concentrations PM2.5 in atmospheric air. Bishkek// Problems of automation and control. - Bishkek: Ilim, 2019. No2(37) -S. 5-15. Gaydamako V.V. Simulation of a cloud information and measurement system using the Simgrid library / / Problems of automation and control. - Bishkek: Ilim, 2019. N1(36)-C. 41-50.Gaidamako V.V., Aveltsov D.O. To the question of methods of increasing the performance of high-load systems // Problems of automation and control. - Bishkek: Ilim, 2019. N1(36)-C. 51-60. Aveltsov D.O. Development of software elements of virtual sensors using containers // Problems of automation and control. - Bishkek: Ilim, 2019 N2(37). 39-50. Fortieth A.V. A text tone analysis system based on the SentiMe LSTM text classifier. Certificate for the computer program No. 575 of August 29, 2019. Bishkek: State Patent Service, 2019.Publications 2018
Velikanova L.I., Lychenko N.M. Restoration of passes in temperature time series based on neural network models // Problems of automation and control. Bishkek: Ilim, 2018. No. 2(35). C. 51-58. Gaydamako V.V. CUDA programming model and virtualization of graphics processors // Problems of automation and control. Bishkek: Ilim, 2018. No. 2(35). 17-26. Gaydamako V.V. Infrastructure sensor-cloud - cloud information and measurement systems // Problems of automation and control. Bishkek: Ilim, 2018. No. 2(35). 109-118. Verzunov S.N., Lychenko N.M. Non-stationary time series forecasting based on multiwavelet polymorphic network // Modeling, optimization and information technology. - T.6, No. 4. Voronezh, 2018. 143-154. Aveltsov D.O. Application of microservice architecture in the development of software systems for monitoring environmental parameters // Problems of automation and control. Bishkek: Ilim, 2018. N1 (34). C. 36-42.Publications 2017
Zamay V.I., Mamatov A.N. Development of a pilot version of the Web application of the system for monitoring the parameters of the natural environment // Problems of automation and control. Bishkek: Ilim, 2017. No. 1(32). C. 69-77. 11 certificates of computer programs of the State Patent Service of the Kyrgyz RepublicPublications 2016
Dobrovolsky N.S., Zamay V.I., Priezzhev V.A. Development of software and hardware of the base station of the monitoring system for the parameters of the natural environment // Problems of automation and control. Bishkek: Ilim, 2016. No. 1. S. 8-14. Zamay V.I., Mamatov A.N., Dobrovolsky N.S. Development of software server system for collecting and transmitting data monitoring parameters of the natural environment // Problems of automation and control. Bishkek: Ilim, 2016. No. 1. S. 27-31. Velikanova L.I. Short-term forecast of flood and mudflow hazards in mountainous areas, taking into account soil humidity // Problems of automation and control. Bishkek: Ilim, 2016. No. 1. S. 15-26. Velikanova L.I. Classifier of weather scenarios based on neural network technologies // Problems of automation and control. Bishkek: Ilim, 2016. No. 2(31). C. 24-33.Innovative development
- Automated monitoring and management systems for water distribution.
- Microservice architecture of environmental monitoring system (ASM POS).
- Hardware and software systems for telemechanics and disaster alerts.
- Neural network models of short-term forecasting of environmental parameters.