Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity

A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil

(2020) Binh Thai Pham et al.   Sustainability

Prediction of Pile Axial Bearing Capacity Using Artificial Neural Network and Random Forest

(2020) Tuan Anh Pham et al.   Applied Sciences-Basel

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

(2019) Panagiotis G. Asteris et al.   Applied Sciences-Basel

Optimization of ANFIS with GA and PSO estimating α ratio in driven piles

(2019) Hossein Moayedi et al.   ENGINEERING WITH COMPUTERS

A hybrid computational intelligence approach for predicting soil shear strength for urban housing construction: a case study at Vinhomes Imperia project, Hai Phong city (Vietnam)

(2019) Viet-Ha Nhu et al.   ENGINEERING WITH COMPUTERS

Optimizing an ANN model with genetic algorithm (GA) predicting load-settlement behaviours of eco-friendly raft-pile foundation (ERP) system

(2019) Longqi Liu et al.   ENGINEERING WITH COMPUTERS

Hybrid Artificial Intelligence Approaches for Predicting Buckling Damage of Steel Columns Under Axial Compression

(2019) Lu Minh Le et al.   Materials

Prediction of Compressive Strength of Geopolymer Concrete Using Entirely Steel Slag Aggregates: Novel Hybrid Artificial Intelligence Approaches

(2019) Dong Dao et al.   Applied Sciences-Basel

Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models

(2019) Hui Chen et al.   Applied Sciences-Basel

Hybrid Artificial Intelligence Approaches for Predicting Critical Buckling Load of Structural Members under Compression Considering the Influence of Initial Geometric Imperfections

(2019) Hai-Bang Ly et al.   Applied Sciences-Basel

Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis

(2019) Binh Thai Pham et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Supervised Machine Learning Techniques to the Prediction of Tunnel Boring Machine Penetration Rate

(2019) Hai Xu et al.   Applied Sciences-Basel

Development of Hybrid Artificial Intelligence Approaches and a Support Vector Machine Algorithm for Predicting the Marshall Parameters of Stone Matrix Asphalt

(2019) Hoang-Long Nguyen et al.   Applied Sciences-Basel

Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete

(2019) Ly et al.   Applied Sciences-Basel

Development of an AI Model to Measure Traffic Air Pollution from Multisensor and Weather Data

(2019) Hai-Bang Ly et al.   SENSORS

Adaptive Network Based Fuzzy Inference System with Meta-Heuristic Optimizations for International Roughness Index Prediction

(2019) Hoang-Long Nguyen et al.   Applied Sciences-Basel

A Gene Expression Programming Model for Predicting Tunnel Convergence

(2019) Mohsen Hajihassani et al.   Applied Sciences-Basel

Development of Hybrid Machine Learning Models for Predicting the Critical Buckling Load of I-Shaped Cellular Beams

(2019) Hai-Bang Ly et al.   Applied Sciences-Basel

Invasive Weed Optimization Technique-Based ANN to the Prediction of Rock Tensile Strength

(2019) Lei Huang et al.   Applied Sciences-Basel

Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach

(2019) Chongchong Qi et al.   CHEMOSPHERE

Krill herd algorithm-based neural network in structural seismic reliability evaluation

(2018) Panagiotis G. Asteris et al.   MECHANICS OF ADVANCED MATERIALS AND STRUCTURES

The Optimal ANN Model for Predicting Bearing Capacity of Shallow Foundations trained on Scarce Data

(2018) Marta Bagińska et al.   KSCE Journal of Civil Engineering

Prediction of bearing capacity of thin-walled foundation: a simulation approach

(2017) Ehsan Momeni et al.   ENGINEERING WITH COMPUTERS

Self-compacting concrete strength prediction using surrogate models

(2017) Panagiotis G. Asteris et al.   NEURAL COMPUTING & APPLICATIONS

State-of-the-art review of some artificial intelligence applications in pile foundations

(2016) Mohamed A. Shahin   Geoscience Frontiers

Application of Artificial Neural Network for Predicting Shaft and Tip Resistances of Concrete Piles

(2015) Ehsan Momeni et al.   Earth Sciences Research Journal

Developing a hybrid PSO–ANN model for estimating the ultimate bearing capacity of rock-socketed piles

(2015) Danial Jahed Armaghani et al.   NEURAL COMPUTING & APPLICATIONS

Prediction of pile bearing capacity using a hybrid genetic algorithm-based ANN

(2014) E. Momeni et al.   MEASUREMENT

Load–settlement modeling of axially loaded steel driven piles using CPT-based recurrent neural networks

(2014) Mohamed A. Shahin   SOILS AND FOUNDATIONS

Intelligent computing for modeling axial capacity of pile foundations

(2010) Mohamed A. Shahin   CANADIAN GEOTECHNICAL JOURNAL

Prediction of pile settlement using artificial neural networks based on standard penetration test data

(2009) F. Pooya Nejad et al.   COMPUTERS AND GEOTECHNICS

Piles shaft capacity from CPT and CPTu data by polynomial neural networks and genetic algorithms

(2008) H. Ardalan et al.   COMPUTERS AND GEOTECHNICS