Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms

Transportation Geotechnics - Tập 30 - Trang 100608 - 2021
Fazal E. Jalal1, Yongfu Xu1, Mudassir Iqbal2, Babak Jamhiri1, Muhammad Faisal Javed3
1Department of Civil Engineering, State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
3Department of Civil Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, KP 22060, Pakistan

Tài liệu tham khảo

Abbaspour, 2019, Reuse of waste tire textile fibers as soil reinforcement, J Cleaner Prod, 207, 1059, 10.1016/j.jclepro.2018.09.253

AL-Khafaji, 1993, Estimation of soil compaction parameters by means of Atterberg limits, Q J Eng Geol Hydrogeol, 26, 359, 10.1144/GSL.QJEGH.1993.026.004.10

Alavi, 2011, A robust data mining approach for formulation of geotechnical engineering systems, Eng Comput: Int J Comput-Aided Eng, 28, 242, 10.1108/02644401111118132

Alavi, 2010, Multi expression programming: a new approach to formulation of soil classification, Eng Comput, 26, 111, 10.1007/s00366-009-0140-7

Alsharef, 2016, Potential of using nanocarbons to stabilize weak soils, Appl Environ Soil Sci, 10.1155/2016/5060531

Ardakani, 2019, Soil compaction parameters prediction using GMDH-type neural network and genetic algorithm, Eur J Environ Civ Eng, 23, 449, 10.1080/19648189.2017.1304269

Armaghani, 2018, Uniaxial compressive strength prediction through a new technique based on gene expression programming, Neural Comput Appl, 30, 3523, 10.1007/s00521-017-2939-2

ASTM 2012. Standard test methods for laboratory compaction characteristics of soil using modified effort.

Azim, 2020, Semi-analytical model for compressive arch action capacity of RC frame structures, Structures, 1231, 10.1016/j.istruc.2020.06.011

Azim, 2020, Prediction model for compressive arch action capacity of RC frame structures under column removal scenario using gene expression programming, Structures, 212, 10.1016/j.istruc.2020.02.028

Benson, 1993, Probability distributions for hydraulic conductivity of compacted soil liners, J Geotech Eng, 119, 471, 10.1061/(ASCE)0733-9410(1993)119:3(471)

Bian, 2019, Voids effect on the swelling behaviour of compacted bentonite, Géotechnique, 69, 593, 10.1680/jgeot.17.P.283

Brown, 2006, The wisdom development scale: Translating the conceptual to the concrete, J College Student Develop, 47, 1, 10.1353/csd.2006.0002

Cabalar, 2009, Genetic programming-based attenuation relationship: an application of recent earthquakes in turkey, Comput Geosci, 35, 1884, 10.1016/j.cageo.2008.10.015

Chen, 2018, Effects of degree of compaction and fines content of the subgrade bottom layer on moisture migration in the substructure of high-speed railways, Proc Instit Mech Eng, Part F: J Rail Rapid Transit, 232, 1197, 10.1177/0954409717710838

Chen, 2021, Experimental study on cyclic settlement of piles in silt soil and its application in high-speed railway design, Transp Geotech, 27, 10.1016/j.trgeo.2020.100496

Delage, 2006, Ageing effects in a compacted bentonite: a microstructure approach, Géotechnique, 56, 291, 10.1680/geot.2006.56.5.291

di Matteo, 2009, Best-fit models to estimate modified proctor properties of compacted soil, J Geotech Geoenviron Eng, 135, 992, 10.1061/(ASCE)GT.1943-5606.0000022

Du, 1999, Swelling–shrinkage properties and soil improvement of compacted expansive soil, Ning-Liang Highway, China, Eng Geol, 53, 351, 10.1016/S0013-7952(98)00086-6

Edjabou, 2017, Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients, Waste Manage, 69, 13, 10.1016/j.wasman.2017.08.036

Farooq, 2016, Prediction of compaction characteristics of fine-grained soils using consistency limits, Arabian J Sci Eng, 41, 1319, 10.1007/s13369-015-1918-0

Gajurel, 2021, Machine learning methods to map stabilizer effectiveness based on common soil properties, Transp Geotech, 27, 10.1016/j.trgeo.2020.100506

Gandomi, 2011, Nonlinear genetic-based models for prediction of flow number of asphalt mixtures, J Mater Civ Eng, 23, 248, 10.1061/(ASCE)MT.1943-5533.0000154

Gandomi, 2015, New design equations for elastic modulus of concrete using multi expression programming, J Civ Eng Manage, 21, 761, 10.3846/13923730.2014.893910

Gandomi, 2015, Assessment of artificial neural network and genetic programming as predictive tools, Adv Eng Softw, 88, 63, 10.1016/j.advengsoft.2015.05.007

Gao, 2018, A comprehensive review on identification of the geomaterial constitutive model using the computational intelligence method, Adv Eng Inf, 38, 420, 10.1016/j.aei.2018.08.021

Garg, 2014, Genomic survey, gene expression analysis and structural modeling suggest diverse roles of DNA methyltransferases in legumes, PLoS ONE, 9, 10.1371/journal.pone.0088947

Güllü, 2014, Function finding via genetic expression programming for strength and elastic properties of clay treated with bottom ash, Eng Appl Artif Intell, 35, 143, 10.1016/j.engappai.2014.06.020

Günaydin, 2009, Estimation of soil compaction parameters by using statistical analyses and artificial neural networks, Environ Geol, 57, 203, 10.1007/s00254-008-1300-6

Iqbal M, Onyelowe KC, Jalal FE. Smart computing models of California bearing ratio, unconfined compressive strength, and resistance value of activated ash-modified soft clay soil with adaptive neuro-fuzzy inference system and ensemble random forest regression techniques. Multiscale and Multidisciplinary Modeling, Experiments and Design, 2021a; 1-19.

Iqbal, 2021, Computational AI prediction models for residual tensile strength of GFRP bars aged in the alkaline concrete environment, Ocean Eng, 232, 10.1016/j.oceaneng.2021.109134

Iqbal, 2020, Prediction of mechanical properties of green concrete incorporating waste foundry sand based on gene expression programming, J Hazard Mater, 384, 10.1016/j.jhazmat.2019.121322

Jalal, 2020, On the Recent Trends in Expansive Soil Stabilization Using Calcium-Based Stabilizer Materials (CSMs): A Comprehensive Review, Adv Mater Sci Eng, 2020, 1510969, 10.1155/2020/1510969

Jalal, 2021, Predictive modeling of swell-strength of expansive soils using artificial intelligence approaches: ANN, ANFIS and GEP, J Environ Manage, 289, 10.1016/j.jenvman.2021.112420

Jędrzejowicz, 2019, Gene Expression Programming as a data classification tool. A review, J Intell Fuzzy Syst, 36, 91, 10.3233/JIFS-18026

Johari, 2006, Prediction of soil–water characteristic curve using genetic programming, J Geotech Geoenviron Eng, 132, 661, 10.1061/(ASCE)1090-0241(2006)132:5(661)

Kaniraj, 2001, Correlation analysis of laboratory compaction of fly ashes, Practice Periodical Hazard, Toxic, Radioactive Waste Manage, 5, 25, 10.1061/(ASCE)1090-025X(2001)5:1(25)

Kataguiri, 2019, Characterization flowchart for assessing the potential reuse of excavation soils in Sao Paulo city, J Cleaner Prod, 240, 10.1016/j.jclepro.2019.118215

Koerner, 2017, Application of linear mixed-effects models in human neuroscience research: a comparison with Pearson correlation in two auditory electrophysiology studies, Brain Sci, 7, 26, 10.3390/brainsci7030026

Koza, 1992

Kurnaz, 2020, The performance comparison of the soft computing methods on the prediction of soil compaction parameters, Arabian J Geosci, 13, 159, 10.1007/s12517-020-5171-9

Landeras, 2012, Comparison of Gene Expression Programming with neuro-fuzzy and neural network computing techniques in estimating daily incoming solar radiation in the Basque Country (Northern Spain), Energy Convers Manage, 62, 1, 10.1016/j.enconman.2012.03.025

Lim, 2004, Wetting-induced compression of compacted Oklahoma soils, J Geotech Geoenviron Eng, 130, 1014, 10.1061/(ASCE)1090-0241(2004)130:10(1014)

Lotfi HA, Schwartz CW, Mitczak MW. Compaction specification for the control of pavement subgrade rutting; 1988.

Mazari, 2016, Prediction of pavement roughness using a hybrid gene expression programming-neural network technique, J Traffic Transport Eng (English Edition), 3, 448, 10.1016/j.jtte.2016.09.007

Miller, 2002, Impact of soil type and compaction conditions on soil water characteristic, J Geotech Geoenviron Eng, 128, 733, 10.1061/(ASCE)1090-0241(2002)128:9(733)

Mohammadzadeh, 2019, Prediction of compression index of fine-grained soils using a gene expression programming model, Infrastructures, 4, 26, 10.3390/infrastructures4020026

Mollahasani, 2011, Empirical modeling of plate load test moduli of soil via gene expression programming, Comput Geotech, 38, 281, 10.1016/j.compgeo.2010.11.008

Moore, 2010

Nash, 1970, River flow forecasting through conceptual models part I—A discussion of principles, J Hydrol, 10, 282, 10.1016/0022-1694(70)90255-6

Omar, 2003, Compaction characteristics of granular soils in United Arab Emirates, Geotech Geol Eng, 21, 283, 10.1023/A:1024927719730

Pearson, 1900, On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling, The London, Edinburgh, Dublin Philos Mag J Sci, 50, 157, 10.1080/14786440009463897

Petry, 2002, Review of stabilization of clays and expansive soils in pavements and lightly loaded structures—history, practice, and future, J Mater Civ Eng, 14, 447, 10.1061/(ASCE)0899-1561(2002)14:6(447)

Pooni, 2021, Performance evaluation of calcium sulfoaluminate as an alternative stabilizer for treatment of weaker subgrades, Transp Geotech, 27, 10.1016/j.trgeo.2020.100462

Portelinha, 2012, Modification of a lateritic soil with lime and cement: an economical alternative for flexible pavement layers, Soils and Rocks, São Paulo, 35, 51, 10.28927/SR.351051

Puth, 2014, Effective use of Pearson's product–moment correlation coefficient, Anim Behav, 93, 183, 10.1016/j.anbehav.2014.05.003

Roy, 2008, On some aspects of variable selection for partial least squares regression models, QSAR Comb Sci, 27, 302, 10.1002/qsar.200710043

Shahin, 2015, Use of evolutionary computing for modelling some complex problems in geotechnical engineering, Geomech Geoeng, 10, 109, 10.1080/17486025.2014.921333

Sharma, 2019, Sustainable deployment of crushed concrete debris and geotextile to improve the load carrying capacity of granular soil, J Cleaner Prod, 228, 124, 10.1016/j.jclepro.2019.04.306

Singh, 2008, Performance evaluation of cement stabilized fly ash–GBFS mixes as a highway construction material, Waste Manage, 28, 1331, 10.1016/j.wasman.2007.09.017

Sivakugan, 2006, Geotechnical considerations in mine backfilling in Australia, J Clean Prod, 14, 1168, 10.1016/j.jclepro.2004.06.007

Smith GN. Probability and statistics in civil engineering. Collins professional and technical books, 244; 1986.

Sridharan, 2004, Swelling behaviour of compacted fine-grained soils, Eng Geol, 72, 9, 10.1016/S0013-7952(03)00161-3

Sridharan, 2005, Plastic limit and compaction characteristics of finegrained soils, Proc Instit Civ Eng-Ground Improvement, 9, 17, 10.1680/grim.2005.9.1.17

Taher, 2020, Comparative assessment of expansive soil stabilization by commercially available polymers, Transp Geotech, 24, 10.1016/j.trgeo.2020.100387

Tchakalova, 2019, Effect of clay content on strength and permeability of plastic loess-cement, Geologica Balcanica, 48, 25, 10.52321/GeolBalc.48.2.25

Terzaghi, 1996

Tziachris, 2019, Assessment of spatial hybrid methods for predicting soil organic matter using DEM derivatives and soil parameters, Catena, 174, 206, 10.1016/j.catena.2018.11.010

Wang, 2018, Permanent deformation of track-bed materials at various inclusion contents under large number of loading cycles, J Geotech Geoenviron Eng, 144, 04018044, 10.1061/(ASCE)GT.1943-5606.0001911

Wang, 2020, High performance prediction of soil compaction parameters using multi expression programming, Eng Geol, 276, 10.1016/j.enggeo.2020.105758

Wang, 2020, Straightforward prediction for air-entry value of compacted soils using machine learning algorithms, Eng Geol, 279, 10.1016/j.enggeo.2020.105911

Wang, 2019, A new empirical formula for evaluating uniaxial compressive strength using the Schmidt hammer test, Int J Rock Mech Min Sci, 123, 10.1016/j.ijrmms.2019.104094

Xu, 2018, Fractal model for the correlation relating total suction to water content of bentonites, Fractals, 26, 1850028, 10.1142/S0218348X18500287

Zhang, 2009, Sediment transport and soil detachment on steep slopes: I. Transport capacity estimation, Soil Sci Soc Am J, 73, 1291, 10.2136/sssaj2008.0145

Zhang, 2020, State-of-the-art review of soft computing applications in underground excavations, Geosci Front, 11, 1095, 10.1016/j.gsf.2019.12.003

Zheng, 2009, Highway subgrade construction in expansive soil areas, J Mater Civ Eng, 21, 154, 10.1061/(ASCE)0899-1561(2009)21:4(154)