Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model
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- @Misc{journals/corr/abs-1907-04913,
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title = "Prediction of Compression Index of Fine-Grained Soils
Using a Gene Expression Programming Model",
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author = "Danial {Mohammadzadeh S.} and Seyed-Farzan Kazemi and
Amir Mosavi and Ehsan Nasseralshariati and
Joseph H. M. Tah",
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howpublished = "arXiv",
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year = "2019",
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volume = "abs/1907.04913",
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keywords = "genetic algorithms, genetic programming, gene
expression programming",
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URL = "http://arxiv.org/abs/1907.04913",
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bibdate = "2019-07-17",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/corr/corr1907.html#abs-1907-04913",
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abstract = "In construction projects, estimation of the settlement
of fine-grained soils is of critical importance, and
yet is a challenging task. The coefficient of
consolidation for the compression index (Cc) is a key
parameter in modeling the settlement of fine-grained
soil layers. However, the estimation of this parameter
is costly, time-consuming, and requires skilled
technicians. To overcome these drawbacks, we aimed to
predict Cc through other soil parameters, i.e., the
liquid limit (LL), plastic limit (PL), and initial void
ratio (e0). Using these parameters is more convenient
and requires substantially less time and cost compared
to the conventional tests to estimate Cc. This study
presents a novel prediction model for the Cc of
fine-grained soils using gene expression programming
(GEP). A database consisting of 108 different data
points was used to develop the model. A closed-form
equation solution was derived to estimate Cc based on
LL, PL, and e0. The performance of the developed
GEP-based model was evaluated through the coefficient
of determination (R2), the root mean squared error
(RMSE), and the mean average error (MAE). The proposed
model performed better in terms of R2, RMSE, and MAE
compared to the other models.",
- }
Genetic Programming entries for
D Mohammadzadeh Shadmehri
Seyed-Farzan Kazemi
Amir Mosavi
Ehsan Nasseralshariati
Joseph H M Tah
Citations