نوع مقاله : مقاله پژوهشی - کاربردی

نویسندگان

گروه ریاضی، دانشگاه پیام نور، تهران، ایران.

10.22105/dmor.2021.278929.1347

چکیده

هدف: ویروس کووید-19 تهدید بزرگی برای سلامتی و ایمنی مردم در سراسر جهان است. یکی از مؤلفه‌های اساسی در مقابله با این تهدید جهانی، تصمیم‌گیری سریع و بجا برای کنترل همه‌گیری این بیماری است؛ بنابراین پیش‌بینی روند آینده این بیماری در جهان ازجمله پیش‌بینی افراد فوت‌شده می‌تواند برای سیاست‌گذاری، مدیریت و کنترل شیوع آن مفید باشد. ازاین‌رو به پیش‌بینی میزان مرگ‌ومیر ناشی از این ویروس با مدل‌های خاکستری در جهان پرداخته‌شده است.
روش‌شناسی پژوهش: این پژوهش به بررسی روند پیش‌بینی میزان مرگ‌ومیر در جهان با استفاده از مدل‌های نظریه سیستم‌های خاکستری می‌پردازد. داده‌های پژوهش از سایت سازمان بهداشت جهانی جمع‌آوری‌شده و پیش‌بینی میزان افراد فوت‌شده در جهان به‌صورت ماهانه با پنج روش سیستم خاکستری GM(1,1)،GreyVerhulst،DGM(1,1)،NGBM(1,1) و F-NGBM(1,1) مدل‌سازی و پیش‌بینی‌شده است. به‌منظور ارزیابی خطای مدل‌ها، از معیارهای متداول ارزیابی خطا MAE، RMSE و MAPE استفاده شد.
یافته ها: با ارزیابی خطای مدل‌ها، پیش‌بینی مدل F-NGBM(1,1) در دسته مدل‌های عالی، مقادیر پیش‌بینی مدل GreyVerhulst جزو دسته پیش‌بینی‌های قابل‌قبول و بقیه مدل‌ها در دسته پیش‌بینی خوب قرار می‌گیرند. همچنین مدل (F-NGBM(1,1 با مقادیر خطایMAE, RMSE و MAPE به ترتیب 26989.54، 21533.94 و 7.21 مناسب‌ترین مدل نسبت به سایر روش‌های دیگر است. 250958 فوتی با پیش‌بینی مدل (F-NGBM(1,1 برای انتهای سال 2021 برآورد شده است که ممکن است مناسب‌ترین مقدار در بین روش‌های پیش‌بینی‌ها باشد.
اصالت/ارزش افزوده علمی: با توجه به عدم وجود داده‌های تاریخی و همچنین عدم قطعیت فراوان در داده‌های دسترس، نیاز است از رویکردهای مواجهه با عدم قطعیت همچون نظریه سیستم خاکستری در پیش‌بینی میزان مرگ‌ومیر این بیماری استفاده شود. ازاین‌رو در این پژوهش برخلاف پژوهش‌های انجام‌شده با مدل‌های مختلف پیش‌بینی خاکستری به برآورد میزان مرگ‌و‌میر پرداخته که به نسبت روش‌های موجود، داده‌های نسبتاً کمتری نیاز داشته و خطای مدل هم بسیار پایین‌تر است. همچنین این پژوهش برای میزان مرگ‌ومیر در کل دنیا انجام‌شده است و جامعیت بیشتری برای اقدامات یکپارچه جهانی خواهد داشت.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Predicting Covid-19 virus mortality in the world by using grey system models

نویسندگان [English]

  • davood darvishi
  • Mostafa Nori joybari
  • parvin babaei

Department of Mathematics, Payame Noor University, P.O. Box 19395-3697, Tehran, Iran

چکیده [English]

Purpose: Covid-19 virus is a major threat to the health and safety of people around the world. One of the key components in dealing with this global threat is rapid and timely decision-making to control the epidemic of the disease, so predicting the future trend of this disease in the world, including predicting deaths, can be useful for policy-making, management and control of its prevalence. Therefore, the mortality rate caused by this virus has been predicted with grey models in the world.
Methodology: This study examines the process of predicting mortality rates in the world using the theory of grey systems models. Research data were collected from the World Health Organization website and predicted the number of deaths in the world on a monthly basis by five methods: GM (1, 1), Verhulst Grey, DGM (1, 1), NGBM (1, 1) and FNGBM(1, 1). In order to evaluate the error of the models, the common error evaluation criteria MAE, RMSE and MAPE were used.
Findings: By evaluating the model error, the prediction of the F-NGBM model (1, 1) in the category of excellent models, the prediction values of the GreyVerhulst model are in the category of acceptable predictions and the rest of the models are in the category of good predictions. Also, the F-NGBM (1, 1) model with MAE, RMSE and MAPE error values of 26989.54, 21533.94 and 7.21, respectively, is the most suitable model compared to the other methods. An estimated 250,958 deaths are estimated by the F-NGBM (1.1) model by the end of 2021, which may be the most appropriate value among forecasting methods.
Originality/Value: Due to the lack of historical data and also a lot of uncertainty in the available data, it is necessary to use approaches to dealing with uncertainty such as the grey system theory in predicting the mortality rate of this disease. Various grey predictions estimate the mortality rate, which requires relatively less data than existing methods, and the model error is much lower. The study also looked at the worldwide mortality rate and will be more comprehensive on integrated global action.

کلیدواژه‌ها [English]

  • Data analysis
  • Covid-19 virus
  • Grey system
  • Grey prediction
  • Time series
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