High performance prediction of soil compaction parameters using multi expression programming
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- @Article{WANG:2020:enggeo,
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author = "Han-Lin Wang and Zhen-Yu Yin",
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title = "High performance prediction of soil compaction
parameters using multi expression programming",
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journal = "Engineering Geology",
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volume = "276",
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pages = "105758",
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year = "2020",
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ISSN = "0013-7952",
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DOI = "doi:10.1016/j.enggeo.2020.105758",
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URL = "http://www.sciencedirect.com/science/article/pii/S0013795220305810",
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keywords = "genetic algorithms, genetic programming, Soil
compaction, Optimum water content, Maximum dry density,
Atterberg limits, Grain size distribution",
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abstract = "Previous prediction models for soil compaction
parameters were developed using limited data of
specific soils and their accuracy also needs to be
improved. This study presents the development of a new
prediction model for the soil compaction parameters
(i.e. optimum water content and maximum dry density)
using the multi expression programming (MEP). Numerous
soil compaction tests with a wide range of soil
classifications and compaction energies are first
collected to form a large database. Then, the optimal
setting of the MEP code parameters is investigated and
determined. The explicit formulations for the two key
compaction parameters are finally proposed. The
validity and the sensitivity analysis of the model are
conducted. The results show that the proposed model
enables to predict the soil compaction parameters for
all kinds of soils in the database with high accuracy.
The monotonicity analysis of the predicted compaction
parameters with each input property (four physical
properties of soil and one compaction energy) verifies
the correctness and the validity of proposed model,
showing consistency with the monotonicity concerning
the actual data in the database. From the sensitivity
analysis about the relevance of each input property on
the predicted compaction parameters, it is indicated
that the plastic limit and the fines content have more
significant influences on the prediction results, while
the effect of the liquid limit is the least
pronounced",
- }
Genetic Programming entries for
Han-Lin Wang
Zhen-Yu Yin
Citations