A Systematic Review of Machine Learning Techniques and Applications in Soil Improvement Using Green Materials

According to an extensive evaluation of published studies, there is a shortage research on systematic literature reviews related machine learning prediction techniques and methodologies in soil improvement using green materials. A review suggests that algorithms are effective at predicting various characteristics, including compressive strength, deformations, bearing capacity, California ratio, compaction performance, stress–strain behavior, geotextile pullout strength classification. The current study aims comprehensively evaluate recent breakthroughs for procedure known as PRISMA meta-analysis. Relevant databases, Web Science, ScienceDirect, IEEE, SCOPUS, were utilized, the chosen papers categorized based on: approach method employed, year publication, authors, journals conferences, goals, findings results, solution modeling. results will advance understanding civil geotechnical designers practitioners integrating data most engineering problems. Additionally, approaches covered this assist strengths weaknesses artificial intelligence compared other traditional mathematical modeling techniques.