A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)

Experimental Investigation of Hybrid Carbon Nanotubes and Graphite Nanoplatelets on Rheology, Shrinkage, Mechanical, and Microstructure of SCCM

(2020) Furqan Farooq et al.   Materials

Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete

(2020) Dong Van Dao et al.   Materials

Toward intelligent construction: Prediction of mechanical properties of manufactured-sand concrete using tree-based models

(2020) Junfei Zhang et al.   JOURNAL OF CLEANER PRODUCTION

Prediction model for compressive arch action capacity of RC frame structures under column removal scenario using gene expression programming

(2020) Iftikhar Azim et al.   Structures

New Prediction Model for the Ultimate Axial Capacity of Concrete-Filled Steel Tubes: An Evolutionary Approach

(2020) Muhammad Faisal Javed et al.   Crystals

Applications of Gene Expression Programming and Regression Techniques for Estimating Compressive Strength of Bagasse Ash based Concrete

(2020) Muhammad Faisal Javed et al.   Crystals

Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete

(2020) Fahid Aslam et al.   Advances in Civil Engineering

Compressive strength prediction of eco-efficient GGBS-based geopolymer concrete using GEP method

(2020) Amir Ali Shahmansouri et al.   Journal of Building Engineering

Artificial neural network model to predict the compressive strength of eco-friendly geopolymer concrete incorporating silica fume and natural zeolite

(2020) Amir Ali Shahmansouri et al.   JOURNAL OF CLEANER PRODUCTION

Prediction of long-term temperature effect in structural health monitoring of concrete dams using support vector machines with Jaya optimizer and salp swarm algorithms

(2019) Fei Kang et al.   ADVANCES IN ENGINEERING SOFTWARE

Prediction model on the compressive strength of recycled aggregate concrete filled steel tube columns

(2019) Abdikarim Idiris Nour et al.   COMPOSITES PART B-ENGINEERING

Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment

(2019) Hao Ling et al.   CONSTRUCTION AND BUILDING MATERIALS

Modeling the compressive strength of high-strength concrete: An extreme learning approach

(2019) Abobakr Khalil Al-Shamiri et al.   CONSTRUCTION AND BUILDING MATERIALS

Modelling uniaxial compressive strength of lightweight self-compacting concrete using random forest regression

(2019) Junfei Zhang et al.   CONSTRUCTION AND BUILDING MATERIALS

A generalized method to predict the compressive strength of high-performance concrete by improved random forest algorithm

(2019) Qinghua Han et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of triaxial behavior of recycled aggregate concrete using multivariable regression and artificial neural network techniques

(2019) Jinjun Xu et al.   CONSTRUCTION AND BUILDING MATERIALS

Ensemble data mining modeling in corrosion of concrete sewer: A comparative study of network-based (MLPNN & RBFNN) and tree-based (RF, CHAID, & CART) models

(2019) Mohammad Zounemat-Kermani et al.   ADVANCED ENGINEERING INFORMATICS

Prediction of mechanical properties of green concrete incorporating waste foundry sand based on gene expression programming

(2019) Muhammad Farjad Iqbal et al.   JOURNAL OF HAZARDOUS MATERIALS

Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model

(2019) Yuantian Sun et al.   Advances in Civil Engineering

Prediction of compressive strength of self-compacting concrete by ANFIS models

(2018) Behnam Vakhshouri et al.   NEUROCOMPUTING

Artificial neural network based modelling approach for strength prediction of concrete incorporating agricultural and construction wastes

(2018) Mulusew Aderaw Getahun et al.   CONSTRUCTION AND BUILDING MATERIALS

Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves

(2018) Ali Behnood et al.   JOURNAL OF CLEANER PRODUCTION

Evaluation of mechanical properties of concretes containing coarse recycled concrete aggregates using multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), and least squares support vector regression (LSSVR) models

(2018) Aliakbar Gholampour et al.   NEURAL COMPUTING & APPLICATIONS

Influence of different types of nano-SiO 2 particles on properties of high-performance concrete

(2016) Alireza Khaloo et al.   CONSTRUCTION AND BUILDING MATERIALS

Modeling of Compressive Strength for Self-Consolidating High-Strength Concrete Incorporating Palm Oil Fuel Ash

(2016) Md. Safiuddin et al.   Materials

Assessment of artificial neural network and genetic programming as predictive tools

(2015) Amir H. Gandomi et al.   ADVANCES IN ENGINEERING SOFTWARE

Predicting stock market index using fusion of machine learning techniques

(2015) Jigar Patel et al.   EXPERT SYSTEMS WITH APPLICATIONS

Machine learning in concrete strength simulations: Multi-nation data analytics

(2014) Jui-Sheng Chou et al.   CONSTRUCTION AND BUILDING MATERIALS

Design for durability: The key to improving concrete sustainability

(2014) R. Doug Hooton et al.   CONSTRUCTION AND BUILDING MATERIALS

Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength

(2013) Jui-Sheng Chou et al.   CONSTRUCTION AND BUILDING MATERIALS

Neural networks analysis of compressive strength of lightweight concrete after high temperatures

(2013) A. Ferhat Bingöl et al.   MATERIALS & DESIGN

Prediction of elastic modulus of normal and high strength concrete using ANFIS and optimal nonlinear regression models

(2012) Behrouz Ahmadi-Nedushan   CONSTRUCTION AND BUILDING MATERIALS

Prediction of compressive strength of recycled aggregate concrete using artificial neural networks

(2012) Z.H. Duan et al.   CONSTRUCTION AND BUILDING MATERIALS

Novel Approach to Strength Modeling of Concrete under Triaxial Compression

(2012) Amir Hossein Gandomi et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Prediction of elastic modulus of normal and high strength concrete by support vector machine

(2010) Kezhen Yan et al.   CONSTRUCTION AND BUILDING MATERIALS

Formulation of flow number of asphalt mixes using a hybrid computational method

(2010) Amir Hossein Alavi et al.   CONSTRUCTION AND BUILDING MATERIALS

Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

(2009) Mohammed Sonebi et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction and multi-objective optimization of high-strength concrete parameters via soft computing approaches

(2008) Adil Baykasoğlu et al.   EXPERT SYSTEMS WITH APPLICATIONS

Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks

(2008) Gregor Trtnik et al.   ULTRASONICS

Prediction of elastic modulus of normal and high strength concrete by artificial neural networks

(2007) Fuat Demir   CONSTRUCTION AND BUILDING MATERIALS