Reactive soils present significant challenges in geotechnical engineering due to their unpredictable behaviour, which can severely impact buildings and infrastructure. While artificial intelligence (AI) has been applied to improve numerical modelling of reactive soils, the scope of its application and future potential remains unclear. AI methods, such as neural networks, support vector machines, genetic algorithms, fuzzy logic...

Deep learning networks were employed to predict the maximum differential deflection of stiffened and waffle rafts due to reactive soil movements, Δ max. Four deep learning networks were used to predict Δ max , these are (1) stiffened rafts on shrinking soil, (2) stiffened rafts on swelling soil, (3) waffle rafts on shrinking soil, and (4) waffle rafts on swelling soil. The deep learning models were used to create design lines,...