نوع مقاله : علمی پژوهشی

نویسندگان

1 استادیار، پژوهشگاه هوافضا، وزارت علوم تحقیقات و فناوری، تهران ،ایران

2 دانشجوی دکتری، دانشگاه آزاد اسلامی واحد علوم و تحقیقات. تهران. ایران.

3 دانشجوی کارشناسی ارشد، گروه مهندسی هوافضا، دانشکده فنی و مهندسی، دانشگاه آزاد اسلامی واحد علوم و تحقیقات، تهران، ایران.

4 دانش آموخته دکتری، دانشگاه آزاد اسلامی واحد علوم و تحقیقات. تهران. ایران.

چکیده

در این مقاله با بهره گیری از الگوریتم ‌یادگیری کیو و روش مقایسات زوجی، مسئله کمبود تجهیزات پایش سلامت در خطوط هوایی به جهت شناسایی بیماران مبتلا به ویروس کووید-19 مورد مطالعه و بررسی قرار گرفته است. در این پژوهش شرکت هواپیمایی کیش ایر به عنوان مورد مطالعاتی بررسی شده است. این مقاله با بررسی مقاصد پروازی شرکت هواپیمایی کیش ایر در طول مدت زمان اوج همه‌گیری ویروس کووید-19 در بهمن ماه سال 1399 با به کارگیری روش مقایسات زوجی و روش یادگیری، میزان ریسک ابتلا به ویروس برای هر مسیر پروازی سنجیده شده است. از طرف دیگر، نحوه توزیع نیروی انسانی و تجهیزات پایش سلامت در این مقاله مورد بررسی قرار گرفته است. نتیجه مدل سازی آماری انجامشده بیانگر ریسک بال تر ابتلا به ویروس کووید-19 در مقاصد پروازی قرار گرفته درمناطق شهری مرکزی ایران در مقایسه با سایر مناطق بوده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Reducing the Prevalence of Coronavirus (COVID-19) in Airlines Based on and the Reinforcement Artificial Intelligence

نویسندگان [English]

  • Iman Shafieenejad 1
  • Mahyar Sadeghi 2
  • Mohammmad Siami Araghi 3
  • Sharareh Ghasemi 4

1 Assistant professor, Aerospace Research Institute, Ministry of Science Research and Technology, Tehran, Iran.

2 PhD. Student, Science and Research Branch. Islamic Azad University. Tehran. Iran.

3 M.Sc. Student، Department of Aerospace Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

4 Ph.D. Holder, Science, and Research Branch. Islamic Azad University.

چکیده [English]

This paper proposes a method based on the artificial intelligence reinforcement Q-learning algorithm and paired comparison technique to solve the problem of health monitoring devices shortage in airlines. In this research, Kish Airline destinations considered as a case study. By considering the importance of continuing air travels during covid-19 pandemic, one of the most effective ways for decreasing the risk of COVID-19 infections in air travels is establishing the health monitoring stations at the airport gates. In view of the enormous number of airports and airlines routes, nationwide coverage of them by health monitoring stations is unimaginable. Therefore, in this paper, artificial intelligence reinforcement Q-learning algorithm functionality in estimating the risk of infecting the COVID-19 virus was considered for the Kish Airline destinations. Furthermore, the optimal policy for the distribution of the health monitoring devices is designed based on the computational model.

کلیدواژه‌ها [English]

  • Corona (COVID-19)
  • Reinforcement Learning
  • Q-learning
  • Pairwise Comparison
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