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    Displacement prediction model of landslide based on multi-gene genetic programming

    New search for: Chen, Jiejie
    New search for: Zeng, Zhigang
    New search for: Jiang, Ping

    In this paper, a new approach is presented for predicting landslide displacement using multi-gene genetic programming (MGGP). For the characteristic of MGGP which does not need specific assumptions, two real cases is used to prove the new approach is feasibility and validity.

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    Displacement prediction model of landslide based on multi-gene genetic programming

    New search for: Chen, Jiejie
    New search for: Zeng, Zhigang
    New search for: Jiang, Ping

    In this paper, a new approach is presented for predicting landslide displacement using multi-gene genetic programming (MGGP). For the characteristic of MGGP which does not need specific assumptions, two real cases is used to prove the new approach is feasibility and validity.

    Access

    Check access
    Check availability in my library
    Order at Subito €

    Displacement prediction model of landslide based on multi-gene genetic programming

    New search for: Chen, Jiejie
    New search for: Zeng, Zhigang
    New search for: Jiang, Ping

    In this paper, a new approach is presented for predicting landslide displacement using multi-gene genetic programming (MGGP). For the characteristic of MGGP which does not need specific assumptions, two real cases is used to prove the new approach is feasibility and validity.

    Access

    Check access
    Check availability in my library
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    Document information
    Title:

    Displacement prediction model of landslide based on multi-gene genetic programming

    Contributors:

    Chen, Jiejie (author) / Zeng, Zhigang (author) / Jiang, Ping (author)

    Published in:

    2016 31st Youth Academic Annual Conference of Chinese Association of Automation (YAC) ; 481-485

    Publication date:

    2016-11-01

    Size:

    219739 byte

    ISBN:

    978-1-5090-4423-8 , 978-1-5090-4422-1

    DOI:

    https://doi.org/10.1109/YAC.2016.7804942

    Type of media:

    Conference paper

    Type of material:

    Electronic Resource

    Language:

    English

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