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A New Evolutionary Approach to Geotechnical and Geo-Environmental Modelling

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Handbook of Genetic Programming Applications

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Abstract

In many cases, models based on certain laws of physics can be developed to describe the behaviour of physical systems. However, in case of more complex phenomena with less known or understood contributing parameters or variables the physics-based modelling techniques may not be applicable. Evolutionary Polynomial Regression (EPR) offers a new way of rendering models, in the form of easily interpretable polynomial equations, explicitly expressing the relationship between contributing parameters of a system of complex nature, and the behaviour of the system. EPR is a recently developed hybrid regression method that provides symbolic expressions for models and works with formulae based on pseudo-polynomial expressions. In this chapter the application of EPR to two important geotechnical and geo-environmental engineering systems is presented. These systems include thermo-mechanical behaviour of unsaturated soils and optimisation of performance of an aquifer system subjected to seawater intrusion. Comparisons are made between the EPR model predictions and the actual measured or synthetic data. The results show that the proposed methodology is able to develop highly accurate models with excellent capability of reflecting the real and expected physical effects of the contributing parameters on the performance of the systems. Merits and advantages of the suggested methodology are highlighted.

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Authors and Affiliations

  1. Department of Engineering, Computational Geomechanics Group, University of Exeter, North Park Road, Exeter, EX4 4QF, UK

    Mohammed S. Hussain & Akbar A. Javadi

  2. School of Computing, Science and Engineering, University of Salford, Newton Building, Peel Park Campus, Salford, Greater Manchester, M5 4WT, UK

    Alireza Ahangar-asr

  3. Department of Civil Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, People’s Republic of China

    Youliang Chen

Authors
  1. Mohammed S. Hussain
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  2. Alireza Ahangar-asr
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  3. Youliang Chen
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  4. Akbar A. Javadi
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Corresponding author

Correspondence to Akbar A. Javadi .

Editor information

Editors and Affiliations

  1. BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, Michigan, USA

    Amir H. Gandomi

  2. Department of Civil & Environmental Engineering, Michigan State University, East Lansing, Michigan, USA

    Amir H. Alavi

  3. Department of Computer Science and Information Systems, University of Limerick, Limerick, Limerick, Ireland

    Conor Ryan

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Hussain, M.S., Ahangar-asr, A., Chen, Y., Javadi, A.A. (2015). A New Evolutionary Approach to Geotechnical and Geo-Environmental Modelling. In: Gandomi, A., Alavi, A., Ryan, C. (eds) Handbook of Genetic Programming Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-20883-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-20883-1_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20882-4

  • Online ISBN: 978-3-319-20883-1

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