Data-driven dynamic clustering framework for mitigating the adverse economic impact of Covid-19 lockdown practices

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Data-driven dynamic clustering framework for mitigating the adverse economic impact of Covid-19 lockdown practices

The COVID-19 disease has once again reiterated the impact of pandemics beyond a biomedical event with potential rapid, dramatic, sweeping disruptions to the management, and conduct of everyday life. Not only the rate and pattern of contagion that threaten our sense of healthy living but also the saf...

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Bibliographic Details
Main Authors:	Rahman, Md. Arafatur, Nafees, Zaman, A. Taufiq, Asyhari, Al-Turjman, Fadi, Alam Bhuiyan, Md. Zakirul, Mohamad Fadli, Zolkipli
Format:	Article
Language:	English English
Published:	Elsevier Ltd 2020
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/29601/ http://umpir.ump.edu.my/id/eprint/29601/1/Data-driven%20dynamic%20clustering%20framework%20for%20mitigating%20the%20adverse%20.pdf http://umpir.ump.edu.my/id/eprint/29601/2/Data-driven%20dynamic%20clustering%20framework%20for%20mitigating%20the%20adverse_FULL.pdf

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