TY - JOUR
T1 - Advancing nanomaterials research
T2 - A comprehensive review of artificial intelligence applications in geotechnical properties
AU - Cemiloglu, Ahmed
AU - Licai, Zhu
AU - Arslan, Sibel
AU - A. Nanehkaran, Yaser
AU - Azarafza, Mohammad
AU - Derakhshani, Reza
PY - 2024/12
Y1 - 2024/12
N2 - This article explores the role of artificial intelligence (AI) in predicting nanomaterial properties, particularly its significance within geotechnical engineering. By analyzing multiple AI-based studies, the review concentrates on the forecasting of nanomaterial-altered soil characteristics and behaviors. Encouraging findings from these studies underscore AI's ability to accurately predict the geotechnical properties of nanomaterials, though challenges remain, particularly in quantifying nanomaterial percentages and their implications across various applications. Future research should address these challenges to enhance the accuracy of AI-based prediction models in geotechnical engineering. Nonetheless, the growing adoption of AI for predicting nanomaterial properties demonstrates its potential to revolutionize geotechnical engineering. AI's capacity to uncover intricate patterns and relationships beyond human capabilities enables more precise soil behavior predictions, fostering innovative solutions to geotechnical challenges. Its ability to process vast datasets, adapt to various scenarios, and continuously learn from new information makes AI an indispensable tool for understanding nanomaterial properties and their impact on soil behavior. In summary, the integration of AI and geotechnical engineering represents a pivotal advancement in comprehending nanomaterial properties and their practical applications. As research advances and AI technologies evolve, transformative progress in geotechnical engineering is expected. By harnessing AI's capabilities, researchers can unlock groundbreaking insights, drive innovation, and shape a more resilient and sustainable future for the geotechnical engineering industry.
AB - This article explores the role of artificial intelligence (AI) in predicting nanomaterial properties, particularly its significance within geotechnical engineering. By analyzing multiple AI-based studies, the review concentrates on the forecasting of nanomaterial-altered soil characteristics and behaviors. Encouraging findings from these studies underscore AI's ability to accurately predict the geotechnical properties of nanomaterials, though challenges remain, particularly in quantifying nanomaterial percentages and their implications across various applications. Future research should address these challenges to enhance the accuracy of AI-based prediction models in geotechnical engineering. Nonetheless, the growing adoption of AI for predicting nanomaterial properties demonstrates its potential to revolutionize geotechnical engineering. AI's capacity to uncover intricate patterns and relationships beyond human capabilities enables more precise soil behavior predictions, fostering innovative solutions to geotechnical challenges. Its ability to process vast datasets, adapt to various scenarios, and continuously learn from new information makes AI an indispensable tool for understanding nanomaterial properties and their impact on soil behavior. In summary, the integration of AI and geotechnical engineering represents a pivotal advancement in comprehending nanomaterial properties and their practical applications. As research advances and AI technologies evolve, transformative progress in geotechnical engineering is expected. By harnessing AI's capabilities, researchers can unlock groundbreaking insights, drive innovation, and shape a more resilient and sustainable future for the geotechnical engineering industry.
KW - artificial intelligence
KW - geotechnical engineering
KW - intelligent models
KW - nanomaterials
KW - prediction
U2 - 10.12989/anr.2024.17.6.485
DO - 10.12989/anr.2024.17.6.485
M3 - Review article
SN - 2287-237X
VL - 17
SP - 485
EP - 499
JO - Advances in Nano Research
JF - Advances in Nano Research
IS - 6
ER -