ArticleISA transactions2022
A novel hybrid fuzzy time series model for prediction of COVID-19 infected cases and deaths in India.
Article in ISA transactions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 44 citations in OpenAlex.
- Forecasting of coronavirus active cases by utilizing logistic growth model and fuzzy time series techniques.Scientific reports · 2024Article
- A Large-Scale IoT-Based Scheme for Real-Time Prediction of Infectious Disease Symptoms.Mobile networks and applications : MONET · 2023Article
- Time-aware sport goods sale prediction for healthcare with privacy-preservation.ISA transactions · 2023Article
- Improved seagull optimization algorithm of partition and XGBoost of prediction for fuzzy time series forecasting of COVID-19 daily confirmed.Advances in engineering software (Barking, London, England : 1992) · 2022Article
- Knowledge-based and data-driven underground pressure forecasting based on graph structure learning.International journal of machine learning and cybernetics · 2022Article
- Analysis of Structured Data in Biomedicine Using Soft Computing Techniques and Computational Analysis.Computational intelligence and neuroscience · 2022Article
- A novel explainable COVID-19 diagnosis method by integration of feature selection with random forest.Informatics in medicine unlocked · 2022Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
World is facing stress due to unpredicted pandemic of novel COVID-19. Daily growing magnitude of confirmed cases of COVID-19 put the whole world humanity at high risk and it has made a pressure on health professionals to get rid of it as soon as possible. So, it becomes necessary to predict the number of upcoming cases in future for the preparation of future plan-of-action and medical set-ups. The present manuscript proposed a hybrid fuzzy time series model for the prediction of upcoming COVID-19 infected cases and deaths in India by using modified fuzzy C-means clustering technique. Proposed model has two phases. In phase-I, modified fuzzy C-means clustering technique is used to form basic intervals with the help of clusters centroid while in phase-II, these intervals are upgraded to form sub-intervals. The proposed model is tested against available COVID-19 data for the measurement of its performance based on mean square error, root mean square error and average forecasting error rate. The novelty of the proposed model lies in the prediction of COVID-19 infected cases and deaths for next coming 31 days. Beside of this, estimation for the approximate number of isolation beds and ICU required has been carried out. The projection of the present model is to provide a base for the decision makers for making protection plan during COVID-19 pandemic.
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