High performance prediction of soil compaction parameters using multi expression programming

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 den...

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Published inEngineering geology Vol. 276; p. 105758
Main Authors Wang, Han-Lin, Yin, Zhen-Yu
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.10.2020
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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. •A new prediction model for the soil compaction parameters is developed using MEP for large number of soils with high accuracy.•The monotonicity analysis with each input parameter verifies the correctness and the validity of proposed model.•The plastic limit and the fines content have more significant influences on the prediction results.
AbstractList 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.
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. •A new prediction model for the soil compaction parameters is developed using MEP for large number of soils with high accuracy.•The monotonicity analysis with each input parameter verifies the correctness and the validity of proposed model.•The plastic limit and the fines content have more significant influences on the prediction results.
ArticleNumber 105758
Author Yin, Zhen-Yu
Wang, Han-Lin
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  givenname: Zhen-Yu
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  email: zhenyu.yin@polyu.edu.hk
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Keywords Optimum water content
Atterberg limits
Maximum dry density
Grain size distribution
Genetic programming
Soil compaction
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Snippet Previous prediction models for soil compaction parameters were developed using limited data of specific soils and their accuracy also needs to be improved....
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SubjectTerms Atterberg limits
energy
Genetic programming
geology
Grain size distribution
liquids
Maximum dry density
Optimum water content
prediction
Soil compaction
water content
Title High performance prediction of soil compaction parameters using multi expression programming
URI https://dx.doi.org/10.1016/j.enggeo.2020.105758
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