Optimization of Artificial Neural Networks for the Prediction of Maximum Bearing Capacity in Reinforced Sand

Historically, major developments in civil engineering have only been possible because of parallel developments in the technology of materials. In geotechnical engineering, polymeric reinforcement materials is a subset of a much larger recent development in civil engineering materials: geosynthetics. Geosynthetics are planar products manufactured from polymeric materials (the synthetic) used with soil, rock, or other geotechnical- related material (the geo) as part of a civil engineering project or system. This paper is devoted to create another parallel development in using these materials by optimizing the ultimate bearing capacity of reinforced soils under strip footing using Artificial Neural Network and Genetic Algorithm.

Optimization of Artificial Neural Networks for the Prediction of Maximum Bearing Capacity in Reinforced Sand Keywords:

Artificial Neural Network , Geosynthetics , Genetic Algorithm , Sand , Bearing Capacity