Volume 12, no. 4Pages 82 - 94

Procedure for Constructing Soft Models of Complex Systems by Time Series

S.I. Suyatinov
The problem of creating models of complex systems for assessing their state is considered. The analysis of approaches to construction of diagnostic models is given and their features are marked. For a complex system with a hierarchical structure, a procedure for constructing the models to assess its state using a scalar time series is proposed. In this case, each hierarchical level is described by a lumped-parameter differential equation. The procedure is based on the concept of soft modelling. The efficiency of the proposed procedure is demonstrated by the example of constructing a model for assessing the state of a complex heart rhythm regulation system.
Full text
complex system; soft modelling; basic models; cardiovascular system.
1. Veshneva I., Singatulin R., Bolshakov A., Chistyakova T., Melnikov L. Model of Formation of the Feedback Channel within Ergatic Systems for Monitoring of Quality of Processes of Formation of Personnel Competences. International Journal for Quality Research, 2015, vol. 9, no. 3, pp. 495-512.
2. Belakhov V.V., Kolodyaznaya V.A., Garabadzhiu A.V., Chistyakova T.B., Smirnov I.A. Application of the Todd-Atherton Synthetic Approach for Chemical Modification of Tetraene Macrolide Antibiotic Lucensomycin. Russian Journal of General Chemistry, 2016, vol. 86, no. 3, pp. 570-578.
3. Veshneva I.V., Chistyakova T.B., Bolshakov A.A. The Status Functions Method for Processing and Interpretation of the Measurement Data of Interactions in the Educational Environment. SPIIRAS Proceedings, 2016. no. 6, pp. 144-166.
4. Buldakov N.S., Buldakova T.I., Suyatinov S.I. Etalon-Photometric Method for Estimation of Tissues Density at X-Ray Images. tProgress in Biomedical Optics and Imaging, 2016, vol. 9917, p. 99171Y. DOI: 10.1117/12.2229539
5. Shalizi C.R. Methods and Techniques of Complex Systems Science: An Overview. Boston, Springer, 2006.
6. Chistyakova T.B., Novozhilova I.V. Intelligence Computer Simulators for Elearning of Specialists of Innovative Industrial Enterprises. Proceedings of the XIX International Conference on Soft Computing and Measurements, 2016, pp. 329-332. DOI: 10.1109/SCM.2016.7519772
7. Chistyakova T.B., Razygrayev A.S., Polosin A.N., Araztaganova A.M. Joint Innovative IT Projects in the Field of Production of Polymeric Sheet Materials. 2016 IEEE 5Th Forum Strategic Partnership of Universities and Enterprises of Hi-Tech Branches, Science. Education. Innovations, 2016, pp. 61-64. DOI: 10.1109/IVForum.2016.7835855
8. Bezruchko B.P., Smirnov D.A. tExtracting Knowledge from Time Series: An Introduction to Nonlinear Empirical Modelling. Berlin, Springer, 2010.
9. Chistyakova T.B., Polosin A.N. Computer Modelling System of Industrial Extruders with Adjustable Configuration for Polymeric Film Quality Control. 2017 IEEE II International Conference on Control in Technical Systems, 2017, pp. 47-50. DOI: 10.1109/CTSYS.2017.8109485
10. Shen K., Proletarsky A.V., Neusypin K.A. Algorithms of Constructing Models for Compensating Navigation Systems of Unmanned Aerial Vehicles. 2016 International Conference on Robotics and Automation Engineering, 2016, pp. 104-108. DOI: 10.1109/ICRAE.2016.7738798
11. Koval' V.A., Osenin V.N., Suyatinov S.I., Torgashova O.Y. Synthesis of Discrete Controller for Construction of a Distributed Controller of Temperature Conditions of Steam Oil Heater. Journal of Computer and Systems Sciences International, 2011, vol. 50, no. 4, pp. 638-653. DOI: 10.1134/S1064230711040125
12. Xu P.C. Differential Phase Space Reconstructed for Chaotic Time Series. Applied Mathematical Modelling, 2009, vol. 33, pp. 999-1013.
13. Buldakova T.I., Suyatinov S.I. Reconstruction Method for Data Protection in Telemedicine Systems. Progress in Biomedical Optics and Imaging, 2014, vol. 9448, p. 94481U. DOI: 10.1117/12.2180644
14. Huanfei Ma, Siyang Leng, Luonan Chen. Data-Based Prediction and Causality Inference of Nonlinear Dynamics. Science Placecountry-Regionchina Mathematics, 2017, vol. 60, pp. 403-420. DOI: 10.1007/s11425-000-0000-0
15. Tronci St., Giona M., Baratti R. Reconstruction of Chaotic Time Series by Neural Models: a Case Study. Neurocomputing, 2003, vol. 55, pp. 581-591.
16. Huanfei Ma, Aihara K., Luonan Chen. Detecting Causality from Nonlinear Dynamics with Short-Term Time Series. Scientific Reports, 2014, vol. 4, p. 7464.
17. Pecora L.M., Moniz L., Nichols J., Carroll T.L. A Unified Approach to Attractor Reconstruction. An Interdisciplinary Journal of Nonlinear Science, 2007, vol. 17, no. 1, pp. 1-9.
18. Basarab M.A., Konnova N.S., Basarab D.A., Matsievskiy D.D. Digital Signal Processing of the Doppler Blood Flow Meter Using the Methods of Nonlinear Dynamics. Progress in Electromagnetics Research Symposium, 2017, pp. 1715-1720. DOI: 10.1109/PIERS.2017.8262026
19. Haken H. Synergetics: An Introduction. Berlin, Springer, 1983.
20. Stefanovska A. Coupled Oscillators: Complex but Not Complicated Cardiovascular and Brain Interactions. tIEEE Engineering in Medicine and Biology Magazine, 2007, vol. 26, no. 6, pp. 25-29.
21. Mehregan M.R., Hosseinzadeh M., Kazemi A. An Application of Soft System Methodology. Procedia - Social and Behavioral Sciences, 2012, vol. 41, pp. 426-433. DOI: 10.1016/j.sbspro.2012.04.051
22. Gupta P., Kulkarni N. An Introduction of Soft Computing Approach Over Hard Computing. International Journal of Latest Trends in Engineering and Technology, 2013, vol. 3, no. 1, pp. 254-258.
23. Sivanandam S.N., Deepa S.N. Principles of Soft Computing. N.Y., Wiley, 2011.
24. Stefanovska A., Lotric M.B., Strle S., Haken H. The Cardiovascular System as Coupled Oscillators? Physiological Measurement, 2001, vol. 22, pp. 535-550.
25. Silvani A., Magosso E., Bastianini S., Lenzi P., Ursino M. Mathematical Modelling of Cardiovascular Coupling: Central Autonomic Commands and Baroreflex Control. Autonomic Neuroscience: Basic and Clinical, 2011, vol. 162, pp. 66-71. DOI: 10.1016/j.autneu.2011.04.003
26. Buldakova T.I., Suyatinov S.I. Registration and Identification of Pulse Signal for Medical Diagnostics. The International Society for Optical Engineering, 2002, vol. 4707, pp. 343-350.
27. Suyatinov S.I. Criteria and Method for Assessing the Functional State of a Human Operator in a Complex Organizational and Technical System. Global Smart Industry Conference, 2018, pp. 1-6. DOI: 10.1109/GloSIC.2018.8570088