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مروری بر کاربرد یادگیری ماشین در مهندسی روسازیهای آسفالتی | ||
| نشریه مهندسی عمران امیرکبیر | ||
| مقاله 6، دوره 57، شماره 10، دی 1404، صفحه 1839-1872 اصل مقاله (1.69 M) | ||
| نوع مقاله: مقاله مروری | ||
| شناسه دیجیتال (DOI): 10.22060/ceej.2026.23492.8175 | ||
| نویسندگان | ||
| محمد مهدی دادایی؛ محمد صالح انتظاری؛ رشید تن زاده* ؛ فریدون مقدس نژاد | ||
| دانشکده مهندسی عمران و محیط زیست، دانشگاه صنعتی امیرکبیر، تهران، ایران | ||
| چکیده | ||
| نواقص روشهای طراحی و اجرای روسازی راهها در کنار برنامههای غیربهینة ترمیمونگهداری آنها، هزینه های جبرانناپذیر اقتصادی و اجتماعی را به همراه داشته است. در این راستا استفاده از دانش و فنآوریهای جدید در مهندسی روسازی اجتنابناپذیر است. هوش مصنوعی، فنآوری نوینی است که برای توسعة ماشینها و الگوریتمهایی که همانند هوش انسان عمل میکنند استفاده میشود. هوش مصنوعی، قابلیت های منحصربهفردی در بهبود فرآیندهای طراحی، اجرا، ترمیم و نگهداری روسازی ارائه دادهاست که نیازمند زمان و هزینه بسیار کمتری نسبت به روشهای سنتی هستند. در این تحقیق با بررسی 150 مقاله علمی معتبر، کاربرد هوش مصنوعی در دستة یادگیری ماشین در مهندسی روسازی مورد بررسی قرار گرفتهاست. تحلیل پژوهشهای موجود نشان داد الگوریتمهای یادگیری ماشین در 7 حوزة پژوهشی از مهندسی روسازی استفاده شدهاند: بهینهسازی طراحی (11% از مطالعات)، پیشبینی عملکرد قیر (8%)، پیشبینی خصوصیات مخلوط آسفالتی (33%)، تشخیص خرابیهای سطح (19%)، طبقهبندی خرابیهای سطح (2%)، پیشبینی شاخصهای عملکردی رویه (21%) و بهینهسازی برنامة عملیات ترمیمونگهداری (6%). همچنین با هدف شناسایی روندهای موجود در ادبیات موضوع و نیز احصاء دستاوردهای محققین، تحلیلهای آماری از فراوانی پژوهشهای منتشرشده در سالهای مختلف، الگوریتمهای استفادهشده در مدلسازی و متغیرهای واردشده جهت پیشبینی عملکرد مخلوط یا روسازی آسفالتی ارائه گردید. این مطالعه نشان داد یادگیری ماشین ابزاری ضروری و جداییناپذیر جهت اجرا، بهبود و بهینهسازی فرآیندهای مختلف طراحی، ساخت، نگهداری و مدیریت روسازی است. لذا گسترش تحلیلهای مبتنی بر هوش مصنوعی و ارزیابی کاربردهای آن در حوزة مهندسی روسازی ضرورت داشته و پیشنیاز شکلگرفتن فنآوریهای لب دانشی از جمله دوقلوهای دیجیتال روسازی است. | ||
| کلیدواژهها | ||
| روسازی آسفالتی؛ هوش مصنوعی؛ یادگیری ماشین؛ شبکه عصبی مصنوعی؛ بهینهسازی | ||
| موضوعات | ||
| مدیریت روسازی | ||
| عنوان مقاله [English] | ||
| A Review of the Applications of Machine Learning in Asphalt Pavement Engineering | ||
| نویسندگان [English] | ||
| M.M Dadaei؛ m.m Entezari؛ Rashid Tanzadeh؛ Fereidoon Moghadas Nejad | ||
| Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| چکیده [English] | ||
| Incorporating deficient design and construction methods in the pavement industry, exacerbated by unoptimized maintenance plans, has led to unprecedented economic and social costs. Therefore, novel technologies and up-to-date science are urgently needed. Artificial Intelligence (AI), one such technology, is used to develop machines and algorithms that mimic the human brain. AI has proven cost- and time-effective in enhancing asphalt pavement design, material production, construction, and maintenance management, compared to traditional solutions. This article delves into the applications of Machine Learning (ML), a subset of AI, in pavement engineering by reviewing 150 related scientific articles. The results show ML has been employed in seven research areas: design optimization (11% of studies), asphalt performance prediction (8%), prediction of asphalt mixture characteristics (33%), detection of surface defects (19%), classification of surface defects (2%), prediction of pavement functional indices (21%), and maintenance plans optimization (6%). Statistical analyses on publication frequency, algorithms used, and input features for predicting performance were presented to outline trends, research gaps, and achievements. It is concluded that ML is an indispensable tool for improving, optimizing, and conducting critical processes in pavement design, material production, construction, and management. Consequently, further research into ML applications in pavement engineering is necessary. This will facilitate the development of cutting-edge technologies like Digital Twins (DTs) for the industry. | ||
| کلیدواژهها [English] | ||
| Asphalt Pavement, Artificial Intelligence, Machine Learning, Artificial Neural Network, Optimization | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 172 تعداد دریافت فایل اصل مقاله: 197 |
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