35 Years of (AI) in Geotechnical Engineering: State of the Art

• Published in: Geotechnical and geological engineering Vol. 39; no. 2; pp. 637 - 690
• Main Author: Ebid, Ahmed M.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.02.2021; Springer Nature B.V
• Subjects: Artificial intelligence; Artificial neural networks; Civil Engineering; Earth and Environmental Science; Earth Sciences; Engineering; Geotechnical engineering; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Mimicry; Neural networks; Optimization; Rock properties; Search algorithms; Soil properties; State-of-the-Art Review; Terrestrial Pollution; Waste Management/Waste Technology; ANN; Fuzzy system; Expert system; EPR; GP; Geotechnical engineering; GA; SVM; PSO; (AI) techniques
• ISSN: 0960-3182; 1573-1529
• DOI: 10.1007/s10706-020-01536-7

It was 35 years ago since the first usage of Artificial Intelligence (AI) technique in geotechnical engineering, during those years many (AI) techniques were developed based in mathematical, statistical and logical concepts, but the breakthrough occurs by mimicking the natural searching and optimization algorithms. This huge development in (AI) techniques reflected on the geotechnical engineering problems. In this research, 626 paper and thesis published in the period from 1984 to 2019 concerned in applying (AI) techniques in geotechnical engineering were collected, filtered, arranged and classified with respect to subject, (AI) technique, publisher and publishing date and stored in a database. The extracted information from the database were tabulated, presented graphically and commented. The main conclusions is that the number of researches in this field increases almost exponentially, the most used (AI) technique is the Artificial Neural Networks and its enhancements where it is presents about half the researches and finally correlating soil and rock properties is the most addressed subject with about 30% of the researches.