A Genetic Programming-Based Approach for the Performance Characteristics Assessment of Stabilized Soil

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InCollection{books/sp/chiong2012/AlaviGM12,

• author = "Amir Hossein Alavi and Amir Hossein Gandomi and Ali Mollahasani",
• title = "A Genetic Programming-Based Approach for the Performance Characteristics Assessment of Stabilized Soil",
• booktitle = "Variants of Evolutionary Algorithms for Real-World Applications",
• publisher = "Springer",
• year = "2012",
• editor = "Raymond Chiong and Thomas Weise and Zbigniew Michalewicz",
• chapter = "9",
• pages = "343--376",
• keywords = "genetic algorithms, genetic programming, Chemical stabilisation, Simulated annealing, Nonlinear modelling",
• isbn13 = "978-3-642-23423-1",
• DOI = "doi:10.1007/978-3-642-23424-8_11",
• abstract = "This chapter presents a variant of genetic programming, namely linear genetic programming (LGP), and a hybrid search algorithm coupling LGP and simulated annealing (SA), called LGP/SA, to predict the performance characteristics of stabilised soil. LGP and LGP/SA relate the unconfined compressive strength (UCS), maximum dry density (MDD), and optimum moisture content (OMC) metrics of stabilised soil to the properties of the natural soil as well as the types and quantities of stabilizing additives. Different sets of LGP and LGP/SA-based prediction models have been separately developed. The contributions of the parameters affecting UCS, MDD, and OMC are evaluated through a sensitivity analysis. A subsequent parametric analysis is carried out and the trends of the results are compared with previous studies. A comprehensive set of data obtained from the literature has been used for developing the models. Experimental results confirm that the accuracy of the proposed models is satisfactory. In particular, the LGP-based models are found to be more accurate than the LGP/SA-based models.",
• affiliation = "School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran",
• bibdate = "2011-11-16",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/books/collections/Chiong2012.html#AlaviGM12",

}

Genetic Programming entries for A H Alavi A H Gandomi Ali Mollahasani

Citations