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An intelligent based-model role to simulate the factor of safe slope by support vector regression

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Abstract

An infrastructure development in landscape and clearing of more vegetated areas have provided huge changes in Malaysia gradually leading to slope instabilities accompanied by enormous environmental effects such as properties and destructions. Thus, prudent practices through vegetation incorporating to use slope stability is an option to the general stabilized technique. Few researches have investigated the effectiveness of vegetative coverings related to slope and soil parameters. The main goal of this study is to provide an intelligent soft computing model to predict the safety factor (FOS) of a slope using support vector regression (SVR). In the other words, SVR has investigated the surface eco-protection techniques for cohesive soil slopes in Guthrie Corridor Expressway stretch through the probabilistic models analysis to highlight the main parameters. The aforementioned analysis has been performed to predict the FOS of a slope, also the estimator’s function has been confirmed by the simulative outcome compared to artificial neural network and genetic programing resulting in a drastic accurate estimation by SVR. Using new analyzing methods like SVR are more purposeful than achieving a starting point by trial and error embedding multiple factors into one in ordinary low-technique software.

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Authors and Affiliations

  1. Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Puteri Azura Sari, Meldi Suhatril & Maryam Safa

  2. Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Normaniza Osman

  3. Department of Civil Engineering, Jubail University College, Royal Commission of Jubail and Yanbu, Jubail, Saudi Arabia

    M. A. Mu’azu

  4. Department of Civil Engineering, School of Engineering, Higher Education Complex of Bam, Bam, Iran

    Hamzeh Dehghani

  5. Department of Civil Engineering, Qeshm International Branch, Islamic Azad University, Qeshm, Iran

    Yadollah Sedghi

  6. Department of Mining Engineering, University of Kashan, Kashan, Iran

    Mahdi Hasanipanah

  7. Sulaimani Polytechnic University, Sulaymaniyah, Iraq

    Karzan Wakil

  8. Facultad de Arquitectura y Urbanismo, Universidad Tecnológica Equinoccial, Calle Rumipamba s/n y Bourgeois, 170508, Quito, Ecuador

    Majid Khorami

  9. Faculty of Engineering, University of Kragujevac, Sestre Janic 6, Kragujevac, 34000, Serbia

    Stefan Djuric

Authors
  1. Puteri Azura Sari
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  2. Meldi Suhatril
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  3. Normaniza Osman
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  4. M. A. Mu’azu
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  5. Hamzeh Dehghani
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  6. Yadollah Sedghi
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  7. Maryam Safa
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  8. Mahdi Hasanipanah
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  9. Karzan Wakil
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  10. Majid Khorami
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  11. Stefan Djuric
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Correspondence to Meldi Suhatril.

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Sari, P.A., Suhatril, M., Osman, N. et al. An intelligent based-model role to simulate the factor of safe slope by support vector regression. Engineering with Computers 35, 1521–1531 (2019). https://doi.org/10.1007/s00366-018-0677-4

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  • DOI: https://doi.org/10.1007/s00366-018-0677-4

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