دانشگاه آزاد اسلامی واحد علوم و تحقیقات

 آمار

تعداد نشریات50
تعداد شماره‌ها2,079
تعداد مقالات19,525
تعداد مشاهده مقاله22,880,933
تعداد دریافت فایل اصل مقاله21,118,479
Rezaeyan, Ramzan, Mohseni, seyyed Saleh, Ala, Samira, Aghababaeipour, sahebeh. (1401). Efficiency of stochastic logistics model in predicting the population infected with HIV in Iran. , (), -. doi: 10.30495/jnrm.2022.67909.2283
Ramzan Rezaeyan; seyyed Saleh Mohseni; Samira Ala; sahebeh Aghababaeipour. "Efficiency of stochastic logistics model in predicting the population infected with HIV in Iran". , , , 1401, -. doi: 10.30495/jnrm.2022.67909.2283
Rezaeyan, Ramzan, Mohseni, seyyed Saleh, Ala, Samira, Aghababaeipour, sahebeh. (1401). 'Efficiency of stochastic logistics model in predicting the population infected with HIV in Iran', , (), pp. -. doi: 10.30495/jnrm.2022.67909.2283
Rezaeyan, Ramzan, Mohseni, seyyed Saleh, Ala, Samira, Aghababaeipour, sahebeh. Efficiency of stochastic logistics model in predicting the population infected with HIV in Iran. , 1401; (): -. doi: 10.30495/jnrm.2022.67909.2283

Efficiency of stochastic logistics model in predicting the population infected with HIV in Iran

Journal of New Researches in Mathematics
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 08 تیر 1401  XML
نوع مقاله: research paper
شناسه دیجیتال (DOI): 10.30495/jnrm.2022.67909.2283
نویسندگان
Ramzan Rezaeyan email orcid 1؛ seyyed Saleh Mohseniorcid 2؛ Samira Ala3؛ sahebeh Aghababaeipour4
1Assistant Professor in Department of mathematics and statistics, Islamic Azad University, Nour Branch
2Assistant Professor in Electrical Eng. Dept., Islamic Azad University, Nour Branch
3Department of Mathematics, Islamic Azad University, Nour Branch, Nour, Iran
4Islamic Azad University, Nour Branch
چکیده
The study of population growth and population forecasting is a major problem in biology. Since

the growth rate is not completely known over time and depends on environmental factors that

are completely random, then all biological populations (virus, humans, bacteria, etc.) have

some kind of random behavior or noise. It is generally referred to as a random process.

The purpose of this article is to predict the number of people living with HIV in Iran based on

a random logistics model and compare it with a non-random (definitive) model. For a case

study to predict the number of AIDS patients in Iran, we considered the population of patients

during the years 1384 to 1394 and with the help of MATLAB program we simulated the

number of patients for the coming years. Comparison of the obtained results with real values

and the results of other models, shows the high accuracy and efficiency of the model.
کلیدواژه‌ها
Stochastic logistics model؛ prediction؛ ITO integral؛ AIDS virus
آمار
تعداد مشاهده مقاله: 118


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب