Procedure for Constructing Soft Models of Complex Systems by Time Series

S. I. Suyatinov

doi:10.14529/mmp190406

Authors

S. I. Suyatinov Bauman Moscow State Technical University

DOI:

https://doi.org/10.14529/mmp190406

Keywords:

complex system, soft modelling, basic models, cardiovascular system

Abstract

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.

Author Biography

S. I. Suyatinov, Bauman Moscow State Technical University

Candidate of Engineering Sciences

References

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.

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.

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.

Buldakov N.S., Buldakova T.I., Suyatinov S.I. Etalon-Photometric Method for Estimation of Tissues Density at X-Ray Images. Progress in Biomedical Optics and Imaging, 2016, vol. 9917, p. 99171Y. DOI: 10.1117/12.2229539

Shalizi C.R. Methods and Techniques of Complex Systems Science: An Overview. Boston, Springer, 2006.

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

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

Bezruchko B.P., Smirnov D.A. Extracting Knowledge from Time Series: An Introduction to Nonlinear Empirical Modelling. Berlin, Springer, 2010.

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

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

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

Xu P.C. Differential Phase Space Reconstructed for Chaotic Time Series. Applied Mathematical Modelling, 2009, vol. 33, pp. 999–1013.

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

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

Tronci St., Giona M., Baratti R. Reconstruction of Chaotic Time Series by Neural Models: a Case Study. Neurocomputing, 2003, vol. 55, pp. 581–591.

Huanfei Ma, Aihara K., Luonan Chen. Detecting Causality from Nonlinear Dynamics with Short-Term Time Series. Scientific Reports, 2014, vol. 4, p. 7464.

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.

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

Haken H. Synergetics: An Introduction. Berlin, Springer, 1983.

Stefanovska A. Coupled Oscillators: Complex but Not Complicated Cardiovascular and Brain Interactions. IEEE Engineering in Medicine and Biology Magazine, 2007, vol. 26, no. 6, pp. 25–29.

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

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.

Sivanandam S.N., Deepa S.N. Principles of Soft Computing. N.Y., Wiley, 2011.

Stefanovska A., Lotric M.B., Strle S., Haken H. The Cardiovascular System as Coupled Oscillators? Physiological Measurement, 2001, vol. 22, pp. 535–550.

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

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.

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