Open AccessA fuzzy graph approach analysis for COVID-19 outbreak
Author(s) -
Nurfarhana Hassan,
Tahir Ahmad,
Azmirul Ashaari,
Siti Rahmah Awang,
Siti Salwana Mamat,
Wan Munirah Wan Mohamad,
Amirul Aizad Ahmad Fuad
Publication year - 2021
Publication title -
results in physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 56
ISSN - 2211-3797
DOI - 10.1016/j.rinp.2021.104267
Subject(s) - chemometrics , outbreak , covid-19 , fourier transform , fourier transform infrared spectroscopy , data mining , computer science , biological system , mathematics , disease , infectious disease (medical specialty) , virology , medicine , machine learning , physics , biology , optics , mathematical analysis
Complex systems require rigorous analysis using effective method, in order to handle and interpret their information. Spectrum produced from Fourier transform infrared (FTIR) instrument is an example of a complex system, due to their overlapped bands and interactions within the spectrum. Thus, chemometrics techniques are required to further analyze the data, in particular, chemometrics fuzzy autocatalytic set (c-FACS). The c-FACS is initially used to analyze the FTIR spectra of gelatins. However, in this study, the c-FACS is generalized and implemented for analysis of Coronavirus disease 2019 (Covid-19), particularly, the pandemic outbreak in Malaysia. The daily Covid-19 cases in states in Malaysia are modeled and analyzed using c-FACS, to observe the trend and severity of the disease in Malaysia. As a result, the classification of severity of zones in Malaysia are identified. The obtained results offer descriptive insight for strategizing purposes in combating the Covid-19 outbreak in Malaysia.
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