TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEM
Background. The paper presents a new timeline branching method in monitoring and modeling systems, with which it is possible to determine the necessary and sufficient number of scenes for decision-making by dividing the situation under consideration into branches with positive, negative and neutr...
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| Format: | Article |
| Language: | English |
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Penza State University Publishing House
2023-09-01
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| Series: | Модели, системы, сети в экономике, технике, природе и обществе |
| Subjects: |
| _version_ | 1827819555440820224 |
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| author | E.A. Dodonova I.N. Dubinina O.K. Golovnin A.V. Ivashchenko |
| author_facet | E.A. Dodonova I.N. Dubinina O.K. Golovnin A.V. Ivashchenko |
| author_sort | E.A. Dodonova |
| collection | DOAJ |
| description | Background. The paper presents a new timeline branching method in monitoring
and modeling systems, with which it is possible to determine the necessary and sufficient
number of scenes for decision-making by dividing the situation under consideration into
branches with positive, negative and neutral scenarios for the development of a complex social
system, which makes it possible to increase the accuracy of the forecast. Materials and
methods. The solution is based on the theory of cross-correlation analysis of odd time series,
which allows you to process chains of events to determine linear and possible causal relationships.
The timeline branching method consists of the following steps: branching, approximation
and adaptive sampling of timelines, or a vector method for supply and demand. Results.
The proposed method has been tested in order to analyze the dynamics of accumulated
statistics on the key parameters "Number of new infections" and "Availability of medical
care for patients with COVID". Conclusions. The proposed method makes it possible to identify
critical scenes, which are important elements in planning, since can then be used to improve
decision support process. |
| first_indexed | 2024-03-12T01:16:31Z |
| format | Article |
| id | doaj.art-477fab159bbc490d8feea639acbe51b5 |
| institution | Directory Open Access Journal |
| issn | 2227-8486 |
| language | English |
| last_indexed | 2024-03-12T01:16:31Z |
| publishDate | 2023-09-01 |
| publisher | Penza State University Publishing House |
| record_format | Article |
| series | Модели, системы, сети в экономике, технике, природе и обществе |
| spelling | doaj.art-477fab159bbc490d8feea639acbe51b52023-09-13T11:09:22ZengPenza State University Publishing HouseМодели, системы, сети в экономике, технике, природе и обществе2227-84862023-09-01210.21685/2227-8486-2023-2-7TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEME.A. Dodonova0I.N. Dubinina1O.K. Golovnin2A.V. Ivashchenko3LLC «Open code»LLC «Open code»Samara National Research UniversitySamara State Medical University of the Ministry of Healthcare of the Russian FederationBackground. The paper presents a new timeline branching method in monitoring and modeling systems, with which it is possible to determine the necessary and sufficient number of scenes for decision-making by dividing the situation under consideration into branches with positive, negative and neutral scenarios for the development of a complex social system, which makes it possible to increase the accuracy of the forecast. Materials and methods. The solution is based on the theory of cross-correlation analysis of odd time series, which allows you to process chains of events to determine linear and possible causal relationships. The timeline branching method consists of the following steps: branching, approximation and adaptive sampling of timelines, or a vector method for supply and demand. Results. The proposed method has been tested in order to analyze the dynamics of accumulated statistics on the key parameters "Number of new infections" and "Availability of medical care for patients with COVID". Conclusions. The proposed method makes it possible to identify critical scenes, which are important elements in planning, since can then be used to improve decision support process.digital transformationsocial systemmonitoringrisk managementtime seriesdecision support |
| spellingShingle | E.A. Dodonova I.N. Dubinina O.K. Golovnin A.V. Ivashchenko TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEM Модели, системы, сети в экономике, технике, природе и обществе digital transformation social system monitoring risk management time series decision support |
| title | TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEM |
| title_full | TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEM |
| title_fullStr | TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEM |
| title_full_unstemmed | TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEM |
| title_short | TIME SCALE BRANCHING METHOD FOR THE SITUATION DEVELOPMENT SIMULATION IN THE DIGITAL HEALTHCARE MONITORING SYSTEM |
| title_sort | time scale branching method for the situation development simulation in the digital healthcare monitoring system |
| topic | digital transformation social system monitoring risk management time series decision support |
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