Function finding via genetic expression programming for strength and elastic properties of clay treated with bottom ash

摘要: In order to understand the treatment of a marginal soil well, underlying input-output relationship on strength and elastic responses due nonlinearity has always been great importance in stabilized mixtures for an optimal design. This paper employs relatively new soft computing approach, genetic expression programming (GEP), formulations unconfined compressive (UCS) elasticity modulus (Es) clay with bottom ash, using database obtained from laboratory tests conducted study. The predictor variables included are ash dosage, dry unit weight, relative compaction, brittleness index energy absorption capacity. results demonstrate that GEP-based formulas UCS Es significantly able predict measured values high degree accuracy against nonlinear behavior (p 0.847). GEP approach is found have better correlation performance as compared regression well. sensitivity analysis parameter shows dominant influence predictions exerted by dosage study reveals potential tool establishing functions identifying key predicting treated ash. Including waste material proposed can also serve environment development recycling sustainability.