Prediction of Compressive Strength of Sustainable Foam Concrete Using Individual and Ensemble Machine Learning Approaches

Predictive modelling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners

(2021) Furqan Farooq et al.   JOURNAL OF CLEANER PRODUCTION

Compressive Strength of Fly-Ash-Based Geopolymer Concrete by Gene Expression Programming and Random Forest

(2021) Mohsin Ali Khan et al.   Advances in Civil Engineering

Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters

(2021) Zhiqiang Lv et al.   Advances in Civil Engineering

Application of Novel Machine Learning Techniques for Predicting the Surface Chloride Concentration in Concrete Containing Waste Material

(2021) Ayaz Ahmad et al.   Materials

A Comparative Study for the Prediction of the Compressive Strength of Self-Compacting Concrete Modified with Fly Ash

(2021) Furqan Farooq et al.   Materials

Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms

(2021) Hongwei Song et al.   CONSTRUCTION AND BUILDING MATERIALS

Geopolymer concrete as sustainable material: A state of the art review

(2021) Furqan Farooq et al.   CONSTRUCTION AND BUILDING MATERIALS

Compressive strength prediction of fly ash-based geopolymer concrete via advanced machine learning techniques

(2021) Ayaz Ahmad et al.   Case Studies in Construction Materials

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

(2020) Dong Van Dao et al.   Materials

Prediction Models for the Mechanical Properties of Self-Compacting Concrete with Recycled Rubber and Silica Fume

(2020) Robert Bušić et al.   Materials

An ensemble multi-step-ahead forecasting system for fine particulate matter in urban areas

(2020) Ida Kalate Ahani 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

A refreshing view of soft computing models for predicting the deflection of reinforced concrete beams

(2020) Chun Bai et al.   APPLIED SOFT COMPUTING

High temporal resolution prediction of street-level PM2.5 and NOx concentrations using machine learning approach

(2020) Zhiyuan Li et al.   JOURNAL OF CLEANER PRODUCTION

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

(2020) Furqan Farooq et al.   Applied Sciences-Basel

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 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

Lightweight foamed concrete as a promising avenue for incorporating waste materials: A review

(2020) Syed Nasir Shah et al.   RESOURCES CONSERVATION AND RECYCLING

Sugarcane bagasse ash-based engineered geopolymer mortar incorporating propylene fibers

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

An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions

(2019) Sehmus Fidan et al.   Advances in Materials Science and Engineering

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

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

Prediction of fresh and hardened properties of self-compacting concrete using support vector regression approach

(2019) Prasenjit Saha et al.   NEURAL COMPUTING & APPLICATIONS

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

Physical and functional characteristics of foam concrete: A review

(2019) Amritha Raj et al.   CONSTRUCTION AND BUILDING MATERIALS

Linear and non-linear SVM prediction for fresh properties and compressive strength of high volume fly ash self-compacting concrete

(2019) Mohammad Azimi-Pour et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning-based compressive strength prediction for concrete: An adaptive boosting approach

(2019) De-Cheng Feng et al.   CONSTRUCTION AND BUILDING MATERIALS

Multi-objective optimization of influential factors on production process of foamed concrete using Box-Behnken approach

(2018) Shervin Asadzadeh et al.   CONSTRUCTION AND BUILDING MATERIALS

Specimen shape and size effects on the concrete compressive strength under static and dynamic tests

(2018) Mei Li et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction model for optimized self-compacting concrete with fly ash using response surface method based on fuzzy classification

(2018) Sundari Selvaraj et al.   NEURAL COMPUTING & APPLICATIONS

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

(2018) Behnam Vakhshouri et al.   NEUROCOMPUTING

Modeling the Fresh and Hardened Stage Properties of Self-Compacting Concrete using Random Kitchen Sink Algorithm

(2018) Dhanya Sathyan et al.   International Journal of Concrete Structures and Materials

A comprehensive study of basalt fiber reinforced magnesium phosphate cement incorporating ultrafine fly ash

(2018) Muhammad Riaz Ahmad et al.   COMPOSITES PART B-ENGINEERING

Self-compacting concrete strength prediction using surrogate models

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

M5' and Mars Based Prediction Models for Properties of Self-compacting Concrete Containing Fly Ash

(2017) Ali Kaveh   Periodica Polytechnica-Civil Engineering

Prediction of self-compacting concrete elastic modulus using two symbolic regression techniques

(2016) Emadaldin Mohammadi Golafshani et al.   AUTOMATION IN CONSTRUCTION

Prediction of self-compacting concrete strength using artificial neural networks

(2016) P.G. Asteris et al.   European Journal of Environmental and Civil Engineering

Prediction of properties of self-compacting concrete containing fly ash using artificial neural network

(2016) Omar Belalia Douma et al.   NEURAL COMPUTING & APPLICATIONS

Assessment of artificial neural network and genetic programming as predictive tools

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

Analyzing the compressive strength of clinker mortars using approximate reasoning approaches - ANN vs MLR

(2015) Ahmet Beycioglu et al.   Computers and Concrete

Properties and applications of foamed concrete; a review

(2015) Y.H. Mugahed Amran et al.   CONSTRUCTION AND BUILDING MATERIALS

Effective use of Pearson's product-moment correlation coefficient: an additional point

(2014) V.J. DeGhett   ANIMAL BEHAVIOUR

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

(2014) Jui-Sheng Chou 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

Prediction of compressive strength of self-compacting concrete containing bottom ash using artificial neural networks

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

Prediction of splitting tensile strength from the compressive strength of concrete using GEP

(2011) Metin Hakan Severcan   NEURAL COMPUTING & APPLICATIONS

Life cycle assessment of building materials: Comparative analysis of energy and environmental impacts and evaluation of the eco-efficiency improvement potential

(2010) Ignacio Zabalza Bribián et al.   BUILDING AND ENVIRONMENT

Proportioning and characterization of lightweight concrete mixtures made with rigid polyurethane foam wastes

(2008) P. Mounanga et al.   CEMENT & CONCRETE COMPOSITES

Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN

(2008) B.K. Raghu Prasad et al.   CONSTRUCTION AND BUILDING MATERIALS

Fresh State Characteristics of Foam Concrete

(2008) E. K. Kunhanandan Nambiar et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Mechanical properties of concrete containing a high volume of tire–rubber particles

(2008) Ali R. Khaloo et al.   WASTE MANAGEMENT