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

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

(2020) Furqan Farooq et al.   Materials

A comparative study on performance evaluation of hybrid GNPs/CNTs in conventional and self-compacting mortar

(2020) Furqan Farooq et al.   Alexandria Engineering Journal

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

Sugarcane bagasse ash-based engineered geopolymer mortar incorporating propylene fibers

(2020) Arslan Akbar et al.   Journal of Building Engineering

Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete

(2019) Dong Dao et al.   Materials

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

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

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

(2019) Abobakr Khalil Al-Shamiri 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 Compressive Strength of Concrete: Critical Comparison of Performance of a Hybrid Machine Learning Model with Standalone Models

(2019) Rachel Cook et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

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 compressive strength of self-compacting concrete by ANFIS models

(2018) Behnam Vakhshouri et al.   NEUROCOMPUTING

Self-compacting concrete strength prediction using surrogate models

(2017) Panagiotis G. Asteris 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

Assessment of artificial neural network and genetic programming as predictive tools

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

Mechanical properties, durability, and life-cycle assessment of self-consolidating concrete mixtures made with blended portland cements containing fly ash and limestone powder

(2015) Kemal Celik et al.   CEMENT & CONCRETE COMPOSITES

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 compressive strength of recycled aggregate concrete using artificial neural networks

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

Prediction of compressive strength of concrete containing construction and demolition waste using artificial neural networks

(2012) Adriana Trocoli Abdon Dantas 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 compressive strength of self-compacting concrete containing bottom ash using artificial neural networks

(2011) Rafat Siddique et al.   ADVANCES IN ENGINEERING SOFTWARE

Predicting the core compressive strength of self-compacting concrete (SCC) mixtures with mineral additives using artificial neural network

(2011) Mucteba Uysal et al.   CONSTRUCTION AND BUILDING MATERIALS

Estimation of compressive strength of self compacting concrete containing polypropylene fiber and mineral additives exposed to high temperature using artificial neural network

(2011) Mucteba Uysal et al.   CONSTRUCTION AND BUILDING MATERIALS

A new prediction model for the load capacity of castellated steel beams

(2011) Amir Hossein Gandomi et al.   JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH

A robust predictive model for base shear of steel frame structures using a hybrid genetic programming and simulated annealing method

(2011) Pejman Aminian et al.   NEURAL COMPUTING & APPLICATIONS

A new multi-gene genetic programming approach to nonlinear system modeling. Part I: materials and structural engineering problems

(2011) Amir Hossein Gandomi et al.   NEURAL COMPUTING & APPLICATIONS

Properties of self-compacting concrete prepared with coarse recycled concrete aggregate

(2010) Zoran Jure Grdic 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

Nonlinear Genetic-Based Models for Prediction of Flow Number of Asphalt Mixtures

(2010) Amir Hossein Gandomi et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

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

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