Genetic programming in civil engineering: advent, applications and future trends
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @Article{Zhang:2021:AIR,
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author = "Qianyun Zhang and Kaveh Barri and Pengcheng Jiao and
Hadi Salehi and Amir H. Alavi",
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title = "Genetic programming in civil engineering: advent,
applications and future trends",
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journal = "Artificial Intelligence Review",
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year = "2021",
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volume = "54",
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pages = "1863--1885",
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month = mar,
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keywords = "genetic algorithms, genetic programming, Civil
engineering, Prediction, Classification, Machine
learning, Deep learning",
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URL = "https://rdcu.be/cwlIF",
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DOI = "doi:10.1007/s10462-020-09894-7",
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size = "23 pages",
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abstract = "Over the past two decades, machine learning has been
gaining significant attention for solving complex
engineering problems. Genetic programming (GP) is an
advanced framework that can be used for a variety of
machine learning tasks. GP searches a program space
instead of a data space without a need to predefined
models. This method generates transparent solutions
that can be easily deployed for practical civil
engineering applications. GP is establishing itself as
a robust intelligent technique to solve complicated
civil engineering problems. We provide a review of the
GP technique and its applications in the civil
engineering arena over the last decade. We discuss the
features of GP and its variants followed by their
potential for solving various civil engineering
problems. We finally envision the potential research
avenues and emerging trends for the application of GP
in civil engineering.",
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notes = "Department of Civil and Environmental Engineering,
University of Pittsburgh, Pittsburgh, PA, USA",
- }
Genetic Programming entries for
Qianyun (Gloria) Zhang
Kaveh Barri
Pengcheng Jiao
Hadi Salehi
A H Alavi
Citations