Pijush Samui

TL;DR: The result shows that the approximation of LSSVM can be used in the FOSM method for slope reliability analysis and is compared with the artificial neural network and least square method.

TL;DR: In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data, which is an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set.

TL;DR: In this article, two statistical learning algorithms (Support Vector Machine and Relevance Vector Machine) were employed for the determination of ultimate bearing capacity (qu) of shallow foundation on cohesionless soil.

TL;DR: It is revealed for the first time an ANN accurately predicting ICU hospitalization and death in COVID‐19 patients, based on genetic variants in complement genes, age and gender, and it is confirmed that genetic dysregulation is associated with impaired complement phenotype.

TL;DR: Experimental results show that the BPNN attained the most accurate prediction of concrete CS based on both ultrasonic pulse velocity and rebound number values, and these two models are very potential to assist engineers in the design phase of civil engineering projects to estimate the concrete CS with a greater accuracy level.