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Fernandez-Marquez, J.L. and Arcos, J.L. (2010) Adapting Particle Swarm Optimization in Dynamic and Noisy Environments. IEEE Congress on Evolutionary Computation, Barcelona, 18-23 July 2010, 1-8.
https://doi.org/10.1109/CEC.2010.5586186

has been cited by the following article:

• TITLE: A Review: Evolutionary Computations (GA and PSO) in Geotechnical Engineering

  AUTHORS: Syed Gous Andrab, Ali Hekmat, Zulkifli Bin Yusop

  KEYWORDS: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Unconfined Seepage, Slope Stability, Foundation Design

  JOURNAL NAME: Computational Water, Energy, and Environmental Engineering, Vol.6 No.2, March 28, 2017

  ABSTRACT: This study briefly reviews the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in geotechnical engineering since GA and PSO are widely used in civil engineering. The application of GA and PSO is studied in three popular families of geotechnical problems including unconfined seepage analysis, slope stability analysis, and foundation design. In each category the available results from different studies are reviewed and compared. The comparison of results shows the desirable accuracy in the predicting of optimal values in the process of analysis and design. The presented methods perform successfully in the reviewed problems. However, PSO predicts the optimum values in fewer numbers of iterations, which suggests higher performance in term of implementation/application.