ArticleSoft computing2023
Optimization using the firefly algorithm of ensemble neural networks with type-2 fuzzy integration for COVID-19 time series prediction.
Article in Soft computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Interval type-2 Fuzzy control and stochastic modeling of COVID-19 spread based on vaccination and social distancing rates.Computer methods and programs in biomedicine · 2023Article
- A new vaccine supply chain network under COVID-19 conditions considering system dynamic: Artificial intelligence algorithms.Socio-economic planning sciences · 2023Article
- An approach for joint optimization of probabilistic group test based on cost and time value: taking nucleic acid detection of COVID-19 as an example.Soft computing · 2023Article
- Interval type-3 fuzzy aggregators for ensembles of neural networks in COVID-19 time series prediction.Engineering applications of artificial intelligence · 2022Article
- Prediction and analysis of COVID-19 daily new cases and cumulative cases: times series forecasting and machine learning models.BMC infectious diseases · 2022Article
- Interval type-2 fuzzy computational model for real time Kalman filtering and forecasting of the dynamic spreading behavior of novel Coronavirus 2019.ISA transactions · 2022Article
- An optimal cascaded recurrent neural network for intelligent COVID-19 detection using Chest X-ray images.Applied soft computing · 2021Article
- Infectivity Upsurge by COVID-19 Viral Variants in Japan: Evidence from Deep Learning Modeling.International journal of environmental research and public health · 2021Article
- Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.IEEE access : practical innovations, open solutions · 2021Article
Corrections and comments
- Retraction · 2024-07-22Concerns/Issues about Referencing/Attributions · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Peer Review · Compromised Peer Review · Investigation by Journal/Publisher · Objections by Author(s) · Rogue Editor · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, the latest global COVID-19 pandemic prediction is addressed. Each country worldwide has faced this pandemic differently, reflected in its statistical number of confirmed and death cases. Predicting the number of confirmed and death cases could allow us to know the future number of cases and provide each country with the necessary information to make decisions based on the predictions. Recent works are focused only on confirmed COVID-19 cases or a specific country. In this work, the firefly algorithm designs an ensemble neural network architecture for each one of 26 countries. In this work, we propose the firefly algorithm for ensemble neural network optimization applied to COVID-19 time series prediction with type-2 fuzzy logic in a weighted average integration method. The proposed method finds the number of artificial neural networks needed to form an ensemble neural network and their architecture using a type-2 fuzzy inference system to combine the responses of individual artificial neural networks to perform a final prediction. The advantages of the type-2 fuzzy weighted average integration (FWA) method over the conventional average method and type-1 fuzzy weighted average integration are shown.
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