نوع مقاله : مقاله پژوهشی
نویسنده
استاد یار جمعیت شناسی دانشکده علوم اجتماعی، دانشگاه تهران، تهران، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسنده [English]
Iran has experienced significant and unique demographic changes in recent decades, influenced by social, economic, and cultural factors that have shifted population dynamics over time. The main aim of this study is to forecast the natural population growth rate—NPG—in Iran over the upcoming decade, from 2025 to 2034, utilizing advanced intelligent deep neural network—DNN—modeling techniques. The goal is to provide a comprehensive and insightful outlook on Iran’s future demographic trends, which can assist policymakers and planners in making informed decisions. To achieve this, key demographic indicators—such as the crude birth rate—CBR—, crude death rate—CDR—, and population doubling time—PDT—have been projected through robust modeling to understand potential future population growth or decline patterns. Simulations were conducted meticulously using MATLAB software, based on accurate data obtained from the Statistical Center of Iran, ensuring reliability and data accuracy. The results indicate that the CBR is expected to decrease from 11.3 per thousand in 2024 to 9.3 per thousand in 2034. Conversely, the CDR is projected to increase from 5.2 per thousand in 2024 to 6.1 per thousand in 2034. Additionally, the NPG is forecasted to decline from 6.1 per thousand in 2024 to 3.2 per thousand in 2034. Finally, the PDT is expected to increase from 114 years in 2024 to 218 years in 2034. However, it should be noted that, in modeling human and behavioral systems, change trends are considered, and precise numerical predictions have limitations. Based on these results, policymakers and planners are advised to implement comprehensive and targeted policies to promote higher fertility and reduce mortality rates, thereby achieving sustainable demographic goals for balanced population development.
کلیدواژهها [English]
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