TY - JOUR
T1 - Estimation of factor of safety of rooted slope using an evolutionary approach
AU - Garg, Akhil
AU - Garg, Ankit
AU - Tai, K.
AU - Sreedeep, S.
PY - 2014/3
Y1 - 2014/3
N2 - Use of roots as one of slope stabilization technique via mechanical reinforcement has received considerable attention in the past few decades. Several mathematical models have been developed to estimate the additional cohesion due to roots, which is useful for the calculation of factor of safety (FOS) of the rooted slopes using finite element method (FEM) or finite difference method. It is well understood from the literature that the root properties such as root area ratio (RAR) and root depth affects the mobilized tensile stress per unit area of soil consequently affecting the FOS of the rooted slope. In addition, a fracture phenomenon also influences the FOS of the rooted slope and should also be considered. In the present work, a new evolutionary approach, namely, multi-gene genetic programming (MGGP) is presented, and, applied to formulate the mathematical relationship between FOS and input variables such as slope angles, root depth and RAR of the rooted slope. The performance of MGGP is compared to those of artificial neural network and support vector regression. Based on the evaluation of the performance of the models, the proposed MGGP model outperformed the two other models and is proved able to capture the characteristics of the FEM model by unveiling important parameters and hidden non-linear relationships.
AB - Use of roots as one of slope stabilization technique via mechanical reinforcement has received considerable attention in the past few decades. Several mathematical models have been developed to estimate the additional cohesion due to roots, which is useful for the calculation of factor of safety (FOS) of the rooted slopes using finite element method (FEM) or finite difference method. It is well understood from the literature that the root properties such as root area ratio (RAR) and root depth affects the mobilized tensile stress per unit area of soil consequently affecting the FOS of the rooted slope. In addition, a fracture phenomenon also influences the FOS of the rooted slope and should also be considered. In the present work, a new evolutionary approach, namely, multi-gene genetic programming (MGGP) is presented, and, applied to formulate the mathematical relationship between FOS and input variables such as slope angles, root depth and RAR of the rooted slope. The performance of MGGP is compared to those of artificial neural network and support vector regression. Based on the evaluation of the performance of the models, the proposed MGGP model outperformed the two other models and is proved able to capture the characteristics of the FEM model by unveiling important parameters and hidden non-linear relationships.
KW - Evolutionary
KW - FOS prediction
KW - GPTIPS
KW - LS-SVM
KW - Multi-gene genetic programming
UR - http://www.scopus.com/inward/record.url?scp=84892838008&partnerID=8YFLogxK
U2 - 10.1016/j.ecoleng.2013.12.047
DO - 10.1016/j.ecoleng.2013.12.047
M3 - Article
AN - SCOPUS:84892838008
SN - 0925-8574
VL - 64
SP - 314
EP - 324
JO - Ecological Engineering
JF - Ecological Engineering
ER -