ArticleHealthcare (Basel, Switzerland)2021
A Novel Method for a COVID-19 Classification of Countries Based on an Intelligent Fuzzy Fractal Approach.
Article in Healthcare (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Fractal dimension based geographical clustering of COVID-19 time series data.Scientific reports · 2023Article
- Picture fuzzy set-based decision-making approach using Dempster-Shafer theory of evidence and grey relation analysis and its application in COVID-19 medicine selection.Soft computing · 2023Article
- Key risk factors associated with fractal dimension based geographical clustering of COVID-19 data in the Flemish and Brussels region, Belgium.Frontiers in public health · 2023Article
- Hybrid harmony search algorithm for social network contact tracing of COVID-19.Soft computing · 2023Article
- Multicriteria group decision making via generalized trapezoidal intuitionistic fuzzy number-based novel similarity measure and its application to diverse COVID-19 scenarios.Artificial intelligence review · 2023Article
- Communicable disease pandemic: a simulation model based on community transmission and social distancing.Soft computing · 2023Article
- Weather indicators and improving air quality in association with COVID-19 pandemic in India.Soft computing · 2023Article
- Expecting individuals' body reaction to Covid-19 based on statistical Naïve Bayes technique.Pattern recognition · 2022Article
- Calibration of Radar RCS Measurement Errors by Observing the Luneburg Lens Onboard the LEO Satellite.Sensors (Basel, Switzerland) · 2022Article
- Forecasting of a complex phenomenon using stochastic data-based techniques under non-conventional schemes: The SARS-CoV-2 virus spread case.Chaos, solitons, and fractals · 2022Article
- Quantum OPTICS and deep self-learning on swarm intelligence algorithms for Covid-19 emergency transportation.Soft computing · 2022Article
- Comparing the dynamics of COVID-19 infection and mortality in the United States, India, and Brazil.Physica D. Nonlinear phenomena · 2022Article
- Article
- COVID-19 pandemic and unemployment rate prediction for developing countries of Asia: A hybrid approach.PloS one · 2022Article
- The selection of COVID-19 epidemic prevention and control programs based on group decision-making.Complex & intelligent systems · 2022Article
- Ambiguous D-means fusion clustering algorithm based on ambiguous set theory: Special application in clustering of CT scan images of COVID-19.Knowledge-based systems · 2021Article
- Predicting the trend of indicators related to Covid-19 using the combined MLP-MC model.Chaos, solitons, and fractals · 2021Article
- Recommending Suitable Smart Technology Applications to Support Mobile Healthcare after the COVID-19 Pandemic Using a Fuzzy Approach.Healthcare (Basel, Switzerland) · 2021Article
- Explaining COVID-19 outbreaks with reactive SEIRD models.Scientific reports · 2021Article
- A novel fractional mathematical model of COVID-19 epidemic considering quarantine and latent time.Results in physics · 2021Article
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2 authors.
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Abstract
We outline in this article a hybrid intelligent fuzzy fractal approach for classification of countries based on a mixture of fractal theoretical concepts and fuzzy logic mathematical constructs. The mathematical definition of the fractal dimension provides a way to estimate the complexity of the non-linear dynamic behavior exhibited by the time series of the countries. Fuzzy logic offers a way to represent and handle the inherent uncertainty of the classification problem. The hybrid intelligent approach is composed of a fuzzy system formed by a set of fuzzy rules that uses the fractal dimensions of the data as inputs and produce as a final output the classification of countries. The hybrid approach calculations are based on the COVID-19 data of confirmed and death cases. The main contribution is the proposed hybrid approach composed of the fractal dimension definition and fuzzy logic concepts for achieving an accurate classification of countries based on the complexity of the COVID-19 time series data. Publicly available datasets of 11 countries have been the basis to construct the fuzzy system and 15 different countries were considered in the validation of the proposed classification approach. Simulation results show that a classification accuracy over 93% can be achieved, which can be considered good for this complex problem.
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