Abstract
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Husnain Ali, Mughees Aslam, Edmund Baffoe-Twum, Abeer Ahmed Jadoon
Abstract
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Comparative analysis of machine learning models for predicting the compressive strength of ultra-high-performance steel fiber reinforced concrete
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A regression-based model for parametric cost estimation of industrial steel structures
10.3846/jcem.2024.22472 · 2024
Predictive analytics for early-stage construction costs estimation
10.3390/buildings12071043 · 2022
Cost and material quantities prediction models for the construction of underground metro stations
10.3390/buildings13020382 · 2023
Managing project scope creep in construction industry
10.1108/ecam-07-2020-0568 · 2022
Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges
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Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
10.1016/j.istruc.2021.06.110 · 2021
Explainable machine learning based efficient prediction tool for lateral cyclic response of post-tensioned base rocking steel bridge piers
10.1016/j.istruc.2022.08.023 · 2022
Mean absolute percentage error for regression models
crossref
Confidence 100%
ror
Confidence 99%
ror
Confidence 99%
openalex
Confidence 95%
datacite
Confidence 0%
10.1016/j.neucom.2015.12.114 · 2016
10.3390/buildings11020066
10.3390/buildings11020066
Properties and material models for modern construction materials at elevated temperatures
10.1016/j.commatsci.2018.12.055 · 2019
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Construction cost estimation of reinforced and prestressed concrete bridges using machine learning
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Modeling and optimization of steel machinability with genetic programming: industrial study
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Early bill-of-quantities estimation of concrete road bridges: an artificial intelligence-based application
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Preliminary engineering cost estimation model for bridge projects
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New prediction models for the compressive strength and dry-thermal conductivity of bio-composites using novel machine learning algorithms
10.1016/j.jclepro.2022.131364 · 2022
Estimation of soil shear strength indicators using soil physical properties of paddy soils in the plastic state
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Material quantity estimation modelling of bridge sub-substructure using regression analysis
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Preliminary cost estimate model for culverts
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Strength-based differential tolerable settlement limits of bridges
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On the search of models for early cost estimates of bridges: an SVM-based approach
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Prediction accuracy in mass appraisal: a comparison of modern approaches
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Effectiveness comparison of the residential property mass appraisal methodologies in the USA
10.1108/17538271111153013 · 2011
Application of linear mixed-effects models in human neuroscience research: a comparison with Pearson correlation in two auditory electrophysiology studies
10.3390/brainsci7030026 · 2017
Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms
10.1016/j.trgeo.2021.100608 · 2021
Effect of soil tillage and vegetal cover on soil water infiltration
10.1016/j.still.2017.07.009 · 2018
Nonlinear genetic-based models for prediction of flow number of asphalt mixtures
10.1061/(asce)mt.1943-5533.0000154 · 2011
A comparative evaluation of various additives used in the stabilization of sulfate bearing lean clay
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A rapid method of determination of swell potential and swell pressure of expansive soils using constant rate of strain apparatus
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A cost estimate method for bridge superstructures using regression analysis and bootstrap
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Parametric model for conceptual cost estimation of concrete bridge foundations
10.1061/(asce)is.1943-555x.0000044 · 2011
Cost estimation model for I-girder bridge superstructure using multiple linear regression and artificial neural network
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Measuring skewness: a forgotten statistic?
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Univariate and multivariate skewness and kurtosis for measuring nonnormality: prevalence, influence and estimation
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Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
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Straightforward prediction for air-entry value of compacted soils using machine learning algorithms
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Comparison of construction cost estimating models based on regression analysis, neural networks, and case-based reasoning
10.1016/j.buildenv.2004.02.013 · doi-reference
A neural network approach for early cost estimation of structural systems of buildings
10.1016/j.ijproman.2004.04.002 · doi-reference
A caution regarding rules of thumb for variance inflation factors
10.1007/s11135-006-9018-6 · doi-reference
Multicollinearity and misleading statistical results
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Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
10.1111/j.1600-0587.2012.07348.x · doi-reference
Univariate and multivariate skewness and kurtosis for measuring nonnormality: prevalence, influence and estimation
10.3758/s13428-016-0814-1 · doi-reference
Measuring skewness: a forgotten statistic?
10.1080/10691898.2011.11889611 · doi-reference
Cost estimation model for I-girder bridge superstructure using multiple linear regression and artificial neural network
10.4028/www.scientific.net/amm.881.142 · doi-reference
Parametric model for conceptual cost estimation of concrete bridge foundations
10.1061/(asce)is.1943-555x.0000044 · doi-reference
A rapid method of determination of swell potential and swell pressure of expansive soils using constant rate of strain apparatus
10.1520/gtj20180414 · doi-reference
A review of techniques for parameter sensitivity analysis of environmental models
10.1007/bf00547132 · doi-reference
A comparative evaluation of various additives used in the stabilization of sulfate bearing lean clay
10.1520/jai101826 · doi-reference
Nonlinear genetic-based models for prediction of flow number of asphalt mixtures
10.1061/(asce)mt.1943-5533.0000154 · doi-reference
Effect of soil tillage and vegetal cover on soil water infiltration
10.1016/j.still.2017.07.009 · doi-reference
Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms
10.1016/j.trgeo.2021.100608 · doi-reference
Application of linear mixed-effects models in human neuroscience research: a comparison with Pearson correlation in two auditory electrophysiology studies
10.3390/brainsci7030026 · doi-reference
Effectiveness comparison of the residential property mass appraisal methodologies in the USA
10.1108/17538271111153013 · doi-reference
Prediction accuracy in mass appraisal: a comparison of modern approaches
10.1080/09599916.2013.781204 · doi-reference
On the search of models for early cost estimates of bridges: an SVM-based approach
10.3390/buildings10010002 · doi-reference
Strength-based differential tolerable settlement limits of bridges
10.1177/1369433217706779 · doi-reference
Preliminary cost estimate model for culverts
10.1016/j.proeng.2015.10.072 · doi-reference
New prediction models for the compressive strength and dry-thermal conductivity of bio-composites using novel machine learning algorithms
10.1016/j.jclepro.2022.131364 · doi-reference
Preliminary engineering cost estimation model for bridge projects
10.1061/(asce)co.1943-7862.0000668 · doi-reference
Early bill-of-quantities estimation of concrete road bridges: an artificial intelligence-based application
10.1177/1087724x17737321 · doi-reference
10.1007/s12559-023-10179-8
10.1007/s12559-023-10179-8 · doi-reference
Modeling and optimization of steel machinability with genetic programming: industrial study
10.3390/met11030426 · doi-reference
Properties and material models for modern construction materials at elevated temperatures
10.1016/j.commatsci.2018.12.055 · doi-reference
10.3390/buildings11020066
10.3390/buildings11020066 · doi-reference
Mean absolute percentage error for regression models
10.1016/j.neucom.2015.12.114 · doi-reference
Explainable machine learning based efficient prediction tool for lateral cyclic response of post-tensioned base rocking steel bridge piers
10.1016/j.istruc.2022.08.023 · doi-reference
Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
10.1016/j.istruc.2021.06.110 · doi-reference
Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges
10.1007/s00163-023-00411-9 · doi-reference
Managing project scope creep in construction industry
10.1108/ecam-07-2020-0568 · doi-reference
Cost and material quantities prediction models for the construction of underground metro stations
10.3390/buildings13020382 · doi-reference
Predictive analytics for early-stage construction costs estimation
10.3390/buildings12071043 · doi-reference
A regression-based model for parametric cost estimation of industrial steel structures
10.3846/jcem.2024.22472 · doi-reference
Comparative analysis of machine learning models for predicting the compressive strength of ultra-high-performance steel fiber reinforced concrete
10.1016/j.jer.2025.01.004 · doi-reference