Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
The Practical Handbook of Genetic Algorithms: Applications, Second Edition
The Practical Handbook of Genetic Algorithms: Applications, Second Edition
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Programming Model for Software Quality Classification
HASE '01 The 6th IEEE International Symposium on High-Assurance Systems Engineering: Special Topic: Impact of Networking
Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)
Evolutionary-based approaches for determining the deviatoric stress of calcareous sands
Computers & Geosciences
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This study investigates an application of genetic programming (GP) for modeling of coarse rotund sand-mica mixtures. An empirical model equation is developed by means of GP technique. The experimental database used for GP modeling is based on a laboratory study of the properties of saturated coarse rotund sand and mica mixtures with various mix ratios under a 100kPa effective stresses, because of its unusual behavior. In the tests, deviatoric stress, and pore pressure generation, and strain have been measured in a 100mm diameter conventional triaxial testing apparatus. The input variables in the developed GP models are the mica content, and strain, and the outputs are deviatoric stress, pore water pressure generation. The performance of accuracies of proposed GP based equations is observed to be quite satisfactory.