Forecasting Models of the Coronavirus (COVID-19) Cumulative Confirmed Cases Using a Hybrid Genetic Programming Method
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- @Article{Salpasaranis_Stylianakis_2020,
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author = "Konstantinos Salpasaranis and Vasilios Stylianakis",
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title = "Forecasting Models of the Coronavirus {(COVID-19)}
Cumulative Confirmed Cases Using a Hybrid Genetic
Programming Method",
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journal = "European Journal of Engineering and Technology
Research",
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year = "2020",
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volume = "5",
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number = "12",
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pages = "52--60",
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month = dec,
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keywords = "genetic algorithms, genetic programming, Evolutionary
algorithms, diffusion models, corona virus,
forecasting",
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URL = "https://www.ej-eng.org/index.php/ejeng/article/view/2129",
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DOI = "doi:10.24018/ejeng.2020.5.12.2129",
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size = "9 pages",
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abstract = "The corona virus disease 2019 (COVID-19) diffusion
process, starting in China, caused more than 4600 lives
until June 2020 and became a major threat to global
public health systems. In Greece, the phenomenon
started on February 2020 and it is still being
developed. This paper presents the implementation of a
hybrid Genetic Programming (hGP) method in finding
fitting models of the Coronavirus (COVID 19) for the
cumulative confirmed cases in China for the first
saturation level until May 2020 and it proposes
forecasting models for Greece before summer tourist
season. The specific hGP method encapsulates the use of
some well-known diffusion models for forecasting
purposes, epidemiological models and produces time
dependent models with high performance statistical
indices. A retrospective study confirmed the excellent
forecasting performance of the method until 3 June
2020.",
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notes = "EJERS",
- }
Genetic Programming entries for
Konstantinos Salpasaranis
Vasilis Stilianakis
Citations