منشور 2024-10-28
الكلمات المفتاحية
- Refugee Health Literacy,
- Trauma-Related Stress,
- Participatory Methodology,
- Mental Health Intervention,
- Integration Barriers
كيفية الاقتباس
الملخص
This overview explores the transformative impact of artificial intelligence (AI) on geotechnical solutions. Traditionally, geotechnical engineering relied on many empirical methods for assessing soil behavior and foundation design. However, with the rapid development and implementation of AI, this field has undergone a significant transformation. AI algorithms, powered by machine learning and data analytics, enable engineers to analyze vast amounts of geotechnical data with unprecedented speed and accuracy. This summary explores how AI algorithms are revolutionizing geotechnical solutions by predicting soil behavior, optimizing foundation designs, and enhancing risk management processes. By harnessing the power of AI, geotechnical engineers can make informed decisions, mitigate risks, and optimize project outcomes like never before.
المراجع
- Guan, Q.Z., Yang, Z.X., Guo, N., Hu, Z., 2023. Finite element geotechnical analysis incorporating deep learning-based soil model. Computers and Geotechnics., 14-105120.
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- Rane, N., Choudhary, S. & Rane, J., 2023. Leading-edge Artificial Intelligence (AI) and Internet of Things (IoT) technologies for enhanced geotechnical site characterization. SSRN Electronic Journal.
- Shahin, M. & Indraratna, B., 2006. Modelling the mechanical behavior of railway ballast using artificial neural networks.. Canadian Geotechnical Journal, 43(11), pp. 1144-1152.
- Shahin, M., 2014. Load-Settlement modeling of axially loaded drilled shafts using CPT-based Recurrent Neural Networks. International Journal of Geomechanics, ASCE, Volume 14, pp. 06014014-1.
- Yi, X. & Wu, J., 2020. Research on Safety Management of Construction Engineering Personnel under “Big Data + Artificial Intelligence”. Open Journal of Business and Management, 8(3), pp. 1059-1075.