نوع مقاله : مقاله پژوهشی - کاربردی
نویسنده
گروه مهندسی برق، دانشگاه فنی و حرفه ای، تهران، ایران.
چکیده
هدف: بیماری کرونا ویروس (کووید-19) یک بیماری همهگیر است که همه کشورهای جهان را درگیر کرده است. پیشبینی روند گسترش بیماری کرونا منجر خواهد شد که تدابیر لازم جهت کنترل این بیماری از سوی مسئولین انجام شود. این موارد شامل افزایش واکسیناسیون، قرنطینه کردن شهرها و ممنوعیت ورود و خروج، افزایش ظرفیت تختهای بیمارستانی، ایجاد مراکز واکسیناسیون شبانهروزی، الزام به استفاده از ماسک در اماکن عمومی و رعایت فواصل اجتماعی بهصورت کلی آمادگی لازم جهت برخورد با پیک جدید بیماری کرونا است. لذا پیشبینی چنین مواردی سبب کاهش آمار مبتلایان به کرونا و لذا کاهش نرخ مرگومیر خواهد شد.
روششناسی پژوهش: در این مقاله با استفاده از آنالیز طیفی منفرد (SSA)، پیشبینی میزان پیک ششم مبتلایان کرونا با لحاظ کردن وضع فعلی صورت گرفته است. بهمنظور بهبود فرآیند گروهبندی الگوریتم SSA، انتخاب مقادیر ویژه بهصورت فرآیند بهینهسازی صورت گرفته است بهطوریکه سری زمانی پیشبینیشده با توجه به شاخص خطای مدنظر بهطور قابلتوجهی بهبود یافته است.
یافتهها: با مقایسه روش پیشنهادی با سایر روشهای پیشبینی شامل میانگین متحرک خود همبسته یکپارچه (ARIMA)، ARIMA کسری (ARFIMA)، TBATS و خود همبسته شبکه عصبی (NNAR)، مشاهده میشود که خطای پیشبینی به حد قابل قبولی بوده و میتواند روش SSA جهت پیشبینی مورد استناد قرار گیرد.
اصالت/ارزشافزوده علمی: در این مقاله با استفاده از روش کارآمد SSA، موارد مبتلا جدید کرونا ویروس را پیشبینی میکند و نتایج ارایه شده اثربخشی روش پیشنهادی را تایید میکند.
کلیدواژهها
موضوعات
عنوان مقاله [English]
Forecasting of COVID-19 sixth peak in Iran based on singular spectrum analysis
نویسنده [English]
- Morteza Abdolhosseini
Department of Electrical Engineering, Technical and Vocational University, Tehran, Iran.
چکیده [English]
Purpose: Coronavirus (COVID-19) is a pandemic that has affected all countries of the world. Forecasting the spread of corona disease will lead to the necessary measures to be taken by the authorities to control this disease. These include increasing vaccinations, quarantining cities and banning entry and exit, increasing the capacity of hospital beds, setting up round-the-clock vaccination centers, requiring the use of masks in public places, and observing social distances. Therefore, predicting such cases will reduce the number of corona cases and therefore reduce the mortality rate.
Methodology: In this paper, using the Singular Spectrum Analysis (SSA) algorithm, the sixth peak of coronavirus in Iran is predicted by considering the current situation. To improve the grouping process of the SSA algorithm, eigenvalues have been selected in the optimization process, so that the predicted time series of which has been significantly improved according to the error-index.
Findings: Comparing the proposed method with other forecasting methods include Autoregressive Integrated Moving Average (ARIMA), Fractional ARIMA (ARFIMA), TBATS, and Neural Network Autoregression (NNAR), it is observed that the forecasting error is acceptable and the SSA method can be used for forecasting.
Originality/Value: This article predicts a new case of COVID-19 using efficient method SSA and the presented results confirm the effectiveness of the proposed method.
کلیدواژهها [English]
- COVID-19
- Corona sixth peak
- Singular spectrum analysis
- Time series forecasting
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