Comparative study of linear regression and SIR models of COVID-19 propagation in Ukraine before vaccination
Abstract
Keywords
Full Text:
PDFReferences
Gorbenko, A., Tarasyuk, O. Exploring timeout as a performance and availability factor of distributed replicated database systems. Radioelectronic and Computer systems, 2020, no. 4 (96), pp. 98-105. DOI: 10.32620/reks.2020.4.09.
Wawrzynski, T. Artificial intelligence and cyberculture. Radioelectronic and Computer systems, 2020, vol. 3, iss. 95, pp. 20-26. DOI: 10.32620/reks.2020.3.02
Izonin, I., Tkachenko, R., Dronyuk, I., Tkachenko, P., Gregus, M., Rashkevych, M. Predictive modeling based on small data in clinical medicine: RBF-based additive input-doubling method. Mathematical Biosciences and Engineering, 2021, vol. 18, iss. 3, pp. 2599-2613. DOI: 10.3934/mbe.2021132.
Liang, J. Multivariate linear regression method based on SPSS analysis of influencing factors of CPI during epidemic situation. 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME), 2020, pp. 294-297, DOI: 10.1109/ICEMME51517.2020.00062.
Li, J. Construction of Big Data Epidemic Forecast and Propagation Model and Analysis of Risk Visualization Trend. 2020 International Conference on Advance in Ambient Computing and Intelligence (ICAACI), 2020, pp. 21-25, DOI: 10.1109/ICAACI50733.2020.00009.
Butov, D., Myasoedov, V., Gumeniuk, M., Gumeniuk, G., Choporova, O., Tkachenko, A., Akymenko, O., Borysova, O., Goptsii, O., Vorobiov, Y., Butova, T. Treatment effectiveness and outcome in patients with a relapse and newly diagnosed multidrug-resistant pulmonary tuberculosis. Medicinski Glasnik, 2020, vol. 17, iss. 2, pp. 356-362. DOI: 10.17392/1179-20.
Bondarenko, A. V., Pokhil, S. I., Lytvynenko, M. V., Bocharova, T. V., Gargin, V. V. Anaplasmosis: Experimental immunodeficient state model, Wiadomosci Lekarskie, 2019, vol. 72, iss. 9-2, pp. 1761-1764.
Kumari, K., Yadav, S. Linear regression analysis study. Journal of the Practice of Cardiovascular Sciences, 2018, vol. 4, iss. 1, pp. 33-36. DOI: 10.4103/jpcs.jpcs_8_18.
Yesina, V., Matveeva, N., Chumachenko, I., Manakova, N. Method of Data Openness Estimation Based on User-Experience in Infocommunication Systems of Municipal Enterprises. 2018 International Scientific-Practical Conference on Problems of Infocommunications Science and Technology, PIC S and T 2018 – Proceedings, 2019, pp. 171–176. DOI: 10.1109/INFOCOMMST.2018.8631897.
Hussein, B. A., Hasson, S. T. A Modeling and Simulation Approach to Analyze and Control Transition States in Epidemic Models. 2019 2nd International Conference on Engineering Technology and its Applications (IICETA), 2019, pp. 94-98, DOI: 10.1109/IICETA47481.2019.9012976.
Dhaka, A., Singh, P. Comparative Analysis of Epidemic Alert System using Machine Learning for Dengue and Chikungunya. 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2020, pp. 798-804, DOI: 10.1109/Confluence47617.2020.9058048.
Jianyi, Y., Chenyang, W., Yupeng, H., Zicheng, L. Research on the relationship between Covid-19 epidemic and gold price trend based on Linear Regression Model. 2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), 2020, pp. 1796-1798. DOI: 10.1109/ITAIC49862.2020.9338828.
Zou, Y., Gong, X., Miao, P., Liu, Y. Using TensorFlow to Establish multivariable linear regression model to Predict Gestational Diabetes. 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), 2020, pp. 1695-1698. DOI: 10.1109/ITNEC48623.2020.9084664.
Sharma, A., Chaudhary, N. Linear Regression Model for Agile Software Development Effort Estimation. 2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2020, pp. 1-4. DOI: 10.1109/ICRAIE51050.2020.9358309.
Fedushko, S., Ustyianovych, T. Operational Intelligence Software Concepts for Continuous Healthcare Monitoring and Consolidated Data Storage Ecosystem. Advances in Intelligent Systems and Computing, 2021, vol. 1247, pp. 545-557. DOI: 10.1007/978-3-030-55506-1_49.
Liu, T. U.S. Pandemic Prediction Using Regression and Neural Network Models. 2020 International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI), 2020, pp. 351-354, DOI: 10.1109/ICHCI51889.2020.00080.
Mandayam, A. U., Siddesha, S., Niranjan, S. K. Prediction of Covid-19 pandemic based on Regression. 2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), 2020, pp. 1-5. DOI: 10.1109/ICRCICN50933.2020.9296175.
Liu, Z., Zuo, J., Lv, R., Sun, Y., Kang, H. Research on Time Series Problem Model Based on Dynamic Network NAR and Multiple Regression. 2020 International Conference on Artificial Intelligence and Computer Engineering (ICAICE), 2020, pp. 416-419. DOI: 10.1109/ICAICE51518.2020.00088.
Xue, H., Bai, Y., Hu, H., Liang, H. Influenza Activity Surveillance Based on Multiple Regression Model and Artificial Neural Network. IEEE Access, 2018, vol. 6, pp. 563-575. DOI: 10.1109/ACCESS.2017.2771798.
Kharchenko, V., Gorbenko, A., Sklyar, V., Phillips, C. Green computing and communications in critical application domains: Challenges and solutions. International Conference on Digital Technologies, 2013, pp. 191-197. DOI: 10.1109/DT.2013.6566310.
Akman, C., Demir, O., Sönmez, T. Covid-19 SEIQR Spread Mathematical Model. 2021 29th Signal Processing and Communications Applications Conference (SIU), 2021, pp. 1-4, DOI: 10.1109/SIU53274.2021.9477975.
Sano, H., Wakaiki, M. State Estimation of Kermack-McKendrick PDE Model With Latent Period and Observation Delay. IEEE Transactions on Automatic Control, 2020, vol. 66, no. 10, pp. 4982-4989. DOI: 10.1109/TAC.2020.3047360.
Guo, Y., Liu, N., Jiao, H. Global stability analysis of a class of SIRS models with nonlinear incidence. 2020 International Conference on Public Health and Data Science (ICPHDS), 2020, pp. 269-272. DOI: 10.1109/ICPHDS51617.2020.00059.
Sokoliuk, A., Kondratenko, G., Sidenko, I., Kondratenko, Y., Khomchenko, A., Atamanyuk, I. Machine Learning Algorithms for Binary Classification of Liver Disease. 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T), 2020, pp. 417-421. DOI: 10.1109/PICST51311.2020.9468051.
Nan, X., Zehong, Z., Zhigeng, P. Dynamic Crowd Aggregation Simulation Using SIR Model Based Emotion Contagion. 2017 International Conference on Virtual Reality and Visualization (ICVRV), 2017, pp. 352-353. DOI: 10.1109/ICVRV.2017.00080
Rodrigues, H. S. Application of SIR epidemiological model: new trends. International Journal of Applied Mathematics and Informatics, 2016, vol. 10, pp. 92-97.
Yeling, L., Jing, W. SIR Infectious Disease Model Based on Age Structure and Constant Migration Rate and its Dynamics Properties. 2020 International Conference on Public Health and Data Science (ICPHDS), 2020, pp. 158-165. DOI: 10.1109/ICPHDS51617.2020.00039.
Yang, Y., Zhang, H. Mathematical Models and Control Methods of Infectious Diseases. 2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE), 2020, pp. 383-388. DOI: 10.1109/CACRE50138.2020.9230170.
Yakovlev, S., Bazilevych, K., Chumachenko, D., Chumachenko, T., Hulianytskyi, L., Meniailov, I., Tkachenko, A. The concept of developing a decision support system for the epidemic morbidity control. CEUR Workshop Proceedings, 2020, vol. 2753, pp. 265–274.
DOI: https://doi.org/10.32620/reks.2021.3.01
Refbacks
- There are currently no refbacks.