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International Journal of Nonlinear Analysis and Applications، جلد ۱۲، شماره ۲، صفحات ۱۲۴۳-۱۲۵۴
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عنوان انگلیسی Modelling covid-19 data using double geometric stochastic process
چکیده انگلیسی مقاله Some properties of the geometric stochastic process (GSP) are studied along with those of a related process which we propose to call the Double geometric stochastic process (DGSP), under certain conditions. This process also has the same advantages of tractability as the geometric stochastic process; it exhibits some properties which may make it a useful complement to the multiple Trends geometric stochastic process. Also, it may be fit to observed data as easily as the geometric stochastic process. As a first attempt, the proposed model was applied to model the data and the Coronavirus epidemic in Iraq to reach the best model that represents the data under study. A chicken swarm optimization algorithm is proposed to choose the best model representing the data, in addition to estimating the parameters a, b, (mu), and (sigma^{2}) of the double geometric stochastic process, where (mu) and (sigma^{2}) are the mean and variance of (X_{1}), respectively.
کلیدواژه‌های انگلیسی مقاله double geometric stochastic process, geometric stochastic process, Parameter estimation, chicken swarm optimization algorithm, multiple monotone trends, root mean square criteria
نویسندگان مقاله Omar R. Jasim |
College of Administration and Economics, University of Al-Hamdaniya, Iraq

Qutaiba N. Nauef |
College of Administration and Economics, University of Bagdad, Iraq

نشانی اینترنتی https://ijnaa.semnan.ac.ir/article_5224_02e9a1bfe58a51b45b35967b11edc6fc.pdf
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