Artificial intelligence design charts for predicting friction capacity of driven pile in clay

Intelligent facial emotion recognition based on stationary wavelet entropy and Jaya algorithm

(2018) Shui-Hua Wang et al.   NEUROCOMPUTING

Tea Category Identification using Computer Vision and Generalized Eigenvalue Proximal SVM

(2017) Shuihua Wang et al.   FUNDAMENTA INFORMATICAE

TWSVR: Regression via Twin Support Vector Machine

(2016) Reshma Khemchandani et al.   NEURAL NETWORKS

A new design chart for estimating friction angle between soil and pile materials

(2016) Huseyin Suha Aksoy et al.   Geomechanics and Engineering

Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC

(2015) Yudong Zhang et al.   Biomedical Signal Processing and Control

Applicability of CPT-based methods in predicting toe bearing capacities of driven piles in sand

(2015) Le Chi Hung et al.   Acta Geotechnica

New method for predicting the ultimate bearing capacity of driven piles by using Flap number

(2014) Fatehnia Milad et al.   KSCE Journal of Civil Engineering

Multivariate adaptive regression spline applied to friction capacity of driven piles in clay

(2013) Pijush Samui   Geomechanics and Engineering

Time dependent behavior of piled raft foundation in clayey soil

(2013) Mohammed Y. Fattah et al.   Geomechanics and Engineering

Resistance factor contour plot analyses of load and resistance factor design of axially-loaded driven piles in clays

(2012) Dongwook Kim et al.   COMPUTERS AND GEOTECHNICS

Modelling load–settlement behaviour of piles using high-order neural network (HON-PILE model)

(2011) A. Ismail et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Generalized eigenvalue proximal support vector regressor

(2011) Reshma Khemchandani et al.   EXPERT SYSTEMS WITH APPLICATIONS

Determination of ultimate capacity of driven piles in cohesionless soil: A Multivariate Adaptive Regression Spline approach

(2011) Pijush Samui   INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS

Applicability of the SPT-based methods for estimating toe bearing capacity of driven PHC piles in the thick deltaic deposits

(2011) N. T. Dung et al.   KSCE Journal of Civil Engineering

Intelligent computing for modeling axial capacity of pile foundations

(2010) Mohamed A. Shahin   CANADIAN GEOTECHNICAL JOURNAL

Neural Network Model for Predicting the Resistance of Driven Piles

(2010) H. I. Park et al.   MARINE GEORESOURCES & GEOTECHNOLOGY

Assessment of the Axial Load Response of an H Pile Driven in Multilayered Soil

(2009) Hoyoung Seo et al.   JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING

TSVR: An efficient Twin Support Vector Machine for regression

(2009) Xinjun Peng   NEURAL NETWORKS

Prediction of friction capacity of driven piles in clay using the support vector machine

(2008) Pijush Samui   CANADIAN GEOTECHNICAL JOURNAL