Modelling Soil Compaction Parameters Using an Enhanced Hybrid Intelligence Paradigm of ANFIS and Improved Grey Wolf Optimiser

The criteria for measuring soil compaction parameters, such as optimum moisture content and maximum dry density, play an important role in construction projects. On sites, base/sub-base soils are compacted at the optimal to achieve desirable level of compaction, generally between 95% 98% density. present technique determining parameters laboratory is a time-consuming task. This study proposes improved hybrid intelligence paradigm alternative tool method estimating density soils. For this purpose, advanced version grey wolf optimiser (GWO) called GWO (IGWO) was integrated with adaptive neuro-fuzzy inference system (ANFIS), which resulted high-performance model named ANFIS-IGWO. Overall, results indicate that proposed ANFIS-IGWO achieved most precise prediction (degree correlation = 0.9203 root mean square error 0.0635) 0.9050 0.0709) outcomes suggested noticeably superior those attained by other ANFIS models, built standard GWO, Moth-flame optimisation, slime mould algorithm, marine predators algorithm. geotechnical engineers can benefit from newly developed during design stage civil engineering MATLAB models also included parameters.