Coronavirus Herd Immunity Optimizer (CHIO)

版本 1.0.0 (5.4 KB) 作者: Mohammed Awadallah
A new nature-inspired human-based optimization algorithm is proposed which is called coronavirus herd immunity optimizer (CHIO).
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The inspiration of CHIO is originated from the herd immunity concept as a way to tackle coronavirus pandemic (COVID-19). The speed of spreading coronavirus infection depends on how the infected individuals directly contact with other society members. In order to protect other members of society from the disease, social distancing is suggested by health experts. Herd immunity is a state the population reaches when most of the population is immune which results in the prevention of disease transmission. These concepts are modeled in terms of optimization concepts. CHIO mimics the herd immunity strategy as well as the social distancing concepts. Three types of individual cases are utilized for herd immunity: susceptible, infected, and immuned. This is to determine how the newly generated solution updates its genes with social distancing strategies.
This is the source codes of the paper: Al-Betar, Mohammed Azmi, Zaid Abdi Alkareem Alyasseri, Mohammed A. Awadallah, and Iyad Abu Doush. "Coronavirus herd immunity optimizer (CHIO)." Neural Computing and Applications 33, no. 10 (2021): 5011-5042. https://doi.org/10.1007/s00521-020-05296-6

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Mohammed Awadallah (2025). Coronavirus Herd Immunity Optimizer (CHIO) (https://www.mathworks.com/matlabcentral/fileexchange/103905-coronavirus-herd-immunity-optimizer-chio), MATLAB Central File Exchange. 检索时间: .

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