Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique

In geotechnical engineering, there is a need to propose a practical, reliable and accurate way for the estimation of pile bearing capacity. A direct measure of this parameter is difficult and expensive to achieve on-site, and needs a series of machine settings. This study aims to introduce a process...

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Autores principales:	Chia Yu Huat, Seyed Mohammad Hossein Moosavi, Ahmed Salih Mohammed, Danial Jahed Armaghani, Dmitrii Vladimirovich Ulrikh, Masoud Monjezi, Sai Hin Lai
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	tree-based techniques feature selection pile bearing capacity gradient boosted tree random forest Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/0d58c96f642c44998a69e6b8029dbab5
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spelling	oai:doaj.org-article:0d58c96f642c44998a69e6b8029dbab52021-11-11T19:33:48ZFactors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique10.3390/su1321118622071-1050https://doaj.org/article/0d58c96f642c44998a69e6b8029dbab52021-10-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/11862https://doaj.org/toc/2071-1050In geotechnical engineering, there is a need to propose a practical, reliable and accurate way for the estimation of pile bearing capacity. A direct measure of this parameter is difficult and expensive to achieve on-site, and needs a series of machine settings. This study aims to introduce a process for selecting the most important parameters in the area of pile capacity and to propose several tree-based techniques for forecasting the pile bearing capacity, all of which are fully intelligent. In terms of the first objective, pile length, hammer drop height, pile diameter, hammer weight, and N values of the standard penetration test were selected as the most important factors for estimating pile capacity. These were then used as model inputs in different tree-based techniques, i.e., decision tree (DT), random forest (RF), and gradient boosted tree (GBT) in order to predict pile friction bearing capacity. This was implemented with the help of 130 High Strain Dynamic Load tests which were conducted in the Kepong area, Malaysia. The developed tree-based models were assessed using various statistical indices and the best performance with the lowest system error was obtained by the GBT technique. The coefficient of determination (R<sup>2</sup>) values of 0.901 and 0.816 for the train and test parts of the GBT model, respectively, showed the power and capability of this tree-based model in estimating pile friction bearing capacity. The GBT model and the input selection process proposed in this research can be introduced as a new, powerful, and practical methodology to predict pile capacity in real projects.Chia Yu HuatSeyed Mohammad Hossein MoosaviAhmed Salih MohammedDanial Jahed ArmaghaniDmitrii Vladimirovich UlrikhMasoud MonjeziSai Hin LaiMDPI AGarticletree-based techniquesfeature selectionpile bearing capacitygradient boosted treerandom forestEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 11862, p 11862 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	tree-based techniques feature selection pile bearing capacity gradient boosted tree random forest Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	tree-based techniques feature selection pile bearing capacity gradient boosted tree random forest Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Chia Yu Huat Seyed Mohammad Hossein Moosavi Ahmed Salih Mohammed Danial Jahed Armaghani Dmitrii Vladimirovich Ulrikh Masoud Monjezi Sai Hin Lai Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique
description	In geotechnical engineering, there is a need to propose a practical, reliable and accurate way for the estimation of pile bearing capacity. A direct measure of this parameter is difficult and expensive to achieve on-site, and needs a series of machine settings. This study aims to introduce a process for selecting the most important parameters in the area of pile capacity and to propose several tree-based techniques for forecasting the pile bearing capacity, all of which are fully intelligent. In terms of the first objective, pile length, hammer drop height, pile diameter, hammer weight, and N values of the standard penetration test were selected as the most important factors for estimating pile capacity. These were then used as model inputs in different tree-based techniques, i.e., decision tree (DT), random forest (RF), and gradient boosted tree (GBT) in order to predict pile friction bearing capacity. This was implemented with the help of 130 High Strain Dynamic Load tests which were conducted in the Kepong area, Malaysia. The developed tree-based models were assessed using various statistical indices and the best performance with the lowest system error was obtained by the GBT technique. The coefficient of determination (R<sup>2</sup>) values of 0.901 and 0.816 for the train and test parts of the GBT model, respectively, showed the power and capability of this tree-based model in estimating pile friction bearing capacity. The GBT model and the input selection process proposed in this research can be introduced as a new, powerful, and practical methodology to predict pile capacity in real projects.
format	article
author	Chia Yu Huat Seyed Mohammad Hossein Moosavi Ahmed Salih Mohammed Danial Jahed Armaghani Dmitrii Vladimirovich Ulrikh Masoud Monjezi Sai Hin Lai
author_facet	Chia Yu Huat Seyed Mohammad Hossein Moosavi Ahmed Salih Mohammed Danial Jahed Armaghani Dmitrii Vladimirovich Ulrikh Masoud Monjezi Sai Hin Lai
author_sort	Chia Yu Huat
title	Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique
title_short	Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique
title_full	Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique
title_fullStr	Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique
title_full_unstemmed	Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique
title_sort	factors influencing pile friction bearing capacity: proposing a novel procedure based on gradient boosted tree technique
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/0d58c96f642c44998a69e6b8029dbab5
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_version_	1718431449934200832

Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique

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