المجلد السادس

العدد الثاني عشر لشهر ديسمبر 2021

رجوع

تحميل البحث

full-text

الملخص:

في وقتنا الحالي، يعد وباء كورونا تهديدًا عالميًا كبيرًا. فلقد أثر على حياة الملايين من الناس حول العالم، و أدى إلى وفاة مئات الآلاف. بناء علي ذلك من المهم التنبؤ بعدد الحالات الجديدة بهدف المساعدة في الوقاية من المرض وكذلك لمساعدة الرعاية الصحية في الاستعداد المبكر لأي طارئ. استخدم العديد من الباحثين طرقًا مختلفة لتعلم الآلة للتنبؤ بالاتجاه المستقبلي للوباء. في هذا البحث تم اقتراح استخدام نموذج الانحدار الذاتي والمتوسط المتحرك للتنبؤ بالحالات الجديدة اليومية في ليبيا على مدى الأشهر الثلاثة المقبلة. حيث تمت معالجة العدد الإجمالي للحالات المؤكدة مسبقًا واستخدامها للتنبؤ بانتشار الفيروس. حيث تم معالجة العدد التراكمي للحالات المؤكدة واستخدامها للتنبؤ بمدي انتشار الفيروس. وبناءً على النتيجة التي تم الحصول عليها من التجربة، من المتوقع أن يرتفع عدد الحالات في المستقبل القريب ليصل إلى 1250 حالة جديدة كل يوم. سيساعد هذا البحث أعضاء الطاقم الطبي والحكومي على التخطيط للظروف القادمة، مما يزيد من جاهزية نظام الرعاية الصحية في البلاد.

Abstract:

Currently, Coronavirus is a major worldwide threat. It has affected millions of people around the world, resulting in hundreds of thousands of deaths. It is indeed important to forecast the number of new cases in aims to assist in disease prevention and healthcare service readiness. Many researchers used different mathematical and machine learning methods to forecast the pandemic's future trend. This research proposes an autoregressive integrated moving average model to forecast the estimated daily new cases in Libya over the next three months. The total number of confirmed cases is pre-processed and used to forecast the virus's spread. The cumulative number of confirmed cases is pre-processed and used to forecast the virus's spread. Based on the result obtained from the experiment, the number of cases expected to rise in the near future, reaching up to 1250 new cases every day. This research would help the government and medical staff members to plan for the upcoming conditions, as a result, increase the readiness of healthcare systems.

Keywords: COVID19, Coronavirus, Pandemic, ARIMA model, Epidemic, forecast, Libya

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