Estimation of the compressive strength of green concretes containing rice husk ash: a comparison of different machine learning approaches

Predicting the compressive strength of self‐compacting concrete containing Class F fly ash using metaheuristic radial basis function neural network

(2021) Gholamreza Pazouki et al.   Structural Concrete

AI-Based Formulation for Mechanical and Workability Properties of Eco-Friendly Concrete Made by Waste Foundry Sand

(2021) Amir Tavana Amlashi et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Predicting the mechanical properties of sustainable concrete containing waste foundry sand using multi-objective ANN approach

(2021) Emadaldin Mohammadi Golafshani et al.   CONSTRUCTION AND BUILDING MATERIALS

Predicting the compressive strength of green concretes using Harris hawks optimization-based data-driven methods

(2021) Emadaldin Mohammadi Golafshani et al.   CONSTRUCTION AND BUILDING MATERIALS

Green mix design of rubbercrete using machine learning-based ensemble model and constrained multi-objective optimization

(2021) Emadaldin Mohammadi Golafshani et al.   Journal of Cleaner Production

Predicting the compressive strength of concrete containing metakaolin with different properties using ANN

(2021) M.J. Moradi et al.   MEASUREMENT

A Sensitivity and Robustness Analysis of GPR and ANN for High-Performance Concrete Compressive Strength Prediction Using a Monte Carlo Simulation

(2020) Dong Van Dao et al.   Sustainability

Machine learning study of the mechanical properties of concretes containing waste foundry sand

(2020) Ali Behnood et al.   CONSTRUCTION AND BUILDING MATERIALS

A metaheuristic-optimized multi-output model for predicting multiple properties of pervious concrete

(2020) Junfei Zhang et al.   CONSTRUCTION AND BUILDING MATERIALS

Application of computational intelligence and statistical approaches for auto-estimating the compressive strength of plastic concrete

(2020) Amir Tavana Amlashi et al.   European Journal of Environmental and Civil Engineering

Experimental investigation and comparative machine-learning prediction of strength behavior of optimized recycled rubber concrete

(2020) Mostafa Jalal et al.   CONSTRUCTION AND BUILDING MATERIALS

Effect of waste rice husk ash from rice husk fuelled brick kilns on strength, durability and thermal performances of mortar

(2020) G.H.M.J. Subashi De Silva et al.   CONSTRUCTION AND BUILDING MATERIALS

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

Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete

(2019) Dong Dao 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

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

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

Optimum model for bearing capacity of concrete-steel columns with AI technology via incorporating the algorithms of IWO and ABC

(2019) Payam Sarir et al.   ENGINEERING WITH COMPUTERS

Soft computing based formulations for slump, compressive strength, and elastic modulus of bentonite plastic concrete

(2019) Amir Tavana Amlashi et al.   JOURNAL OF CLEANER PRODUCTION

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

Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer

(2019) Emadaldin Mohammadi Golafshani 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

A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete

(2018) Dac-Khuong Bui et al.   CONSTRUCTION AND BUILDING MATERIALS

A novel optimised self-learning method for compressive strength prediction of high performance concrete

(2018) Yang Yu et al.   CONSTRUCTION AND BUILDING MATERIALS

Application of soft computing methods for predicting the elastic modulus of recycled aggregate concrete

(2018) Emadaldin Mohammadi Golafshani et al.   JOURNAL OF CLEANER PRODUCTION

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

(2018) Behnam Vakhshouri et al.   NEUROCOMPUTING

M5P model tree based fast fuzzy maximum power point tracker

(2018) Sid-ali Blaifi et al.   SOLAR ENERGY

Modeling of bentonite/sepiolite plastic concrete compressive strength using artificial neural network and support vector machine

(2018) Ali Reza Ghanizadeh et al.   Frontiers of Structural and Civil Engineering

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

Hybrid ultrasonic-neural prediction of the compressive strength of environmentally friendly concrete screeds with high volume of waste quartz mineral dust

(2018) Łukasz Sadowski et al.   JOURNAL OF CLEANER PRODUCTION

Effect of sand content on strength and pore structure of cement mortar

(2017) Jingwu Bu et al.   JOURNAL OF WUHAN UNIVERSITY OF TECHNOLOGY-MATERIALS SCIENCE EDITION

Estimation of physical, mechanical and hydrological properties of permeable concrete using computational intelligence approach

(2016) Adeshina A. Adewumi et al.   APPLIED SOFT COMPUTING

Rice husk ash-based silica-supported iron catalyst coupled with Fenton-like process for the abatement of rice mill wastewater

(2016) Anuj Kumar et al.   Clean Technologies and Environmental Policy

A life-cycle approach to environmental, mechanical, and durability properties of “green” concrete mixes with rice husk ash

(2016) Aysegul Petek Gursel et al.   JOURNAL OF CLEANER PRODUCTION

A review of waste products utilized as supplements to Portland cement in concrete

(2016) Jerry M. Paris et al.   JOURNAL OF CLEANER PRODUCTION

Modelling of compressive strength of geopolymer paste, mortar and concrete by optimized support vector machine

(2015) Ali Nazari et al.   CERAMICS INTERNATIONAL

Evaluation of the splitting tensile strength in plain and steel fiber-reinforced concrete based on the compressive strength

(2015) Ali Behnood et al.   CONSTRUCTION AND BUILDING MATERIALS

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

High-performance concrete compressive strength prediction using Genetic Weighted Pyramid Operation Tree (GWPOT)

(2013) Min-Yuan Cheng et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Effect of specimen size and shape on compressive strength of concrete containing fly ash: Application of genetic programming for design

(2013) Mustafa Sarıdemir   MATERIALS & DESIGN

Strength and Some Durability Properties of Concrete Containing Rice Husk Ash Produced in a Charcoal Incinerator at Low Specific Surface

(2013) A. E. Abalaka   International Journal of Concrete Structures and Materials

High performance concrete compressive strength forecasting using ensemble models based on discrete wavelet transform

(2012) Halil Ibrahim Erdal et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

PREDICTION OF STRENGTH AND SLUMP OF RICE HUSK ASH INCORPORATED HIGH-PERFORMANCE CONCRETE

(2012) Md. Nazrul Islam et al.   Journal of Civil Engineering and Management

Mechanical properties and durability assessment of rice husk ash concrete

(2011) Rahmat Madandoust et al.   BIOSYSTEMS ENGINEERING

Effect of rice husk ash on the strength and durability characteristics of concrete

(2011) Hwang Chao-Lung et al.   CONSTRUCTION AND BUILDING MATERIALS

Reduction in environmental problems using rice-husk ash in concrete

(2011) Rawaid Khan et al.   CONSTRUCTION AND BUILDING MATERIALS

Compressive strength and durability properties of Rice Husk Ash concrete

(2011) V. Ramasamy   KSCE Journal of Civil Engineering

Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques

(2010) Jui-Sheng Chou et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Study on properties of rice husk ash and its use as cement replacement material

(2010) Ghassan Abood Habeeb et al.   Materials Research-Ibero-american Journal of Materials

Mechanical Properties and Durability of Normal and Water Reduced High Strength Grade 60 Concrete Containing Rice Husk Ash

(2009) Hilmi Bin Mahmud et al.   Journal of Advanced Concrete Technology

Prediction of mechanical properties of recycled aggregate concretes containing silica fume using artificial neural networks and fuzzy logic

(2007) İlker Bekir Topçu et al.   COMPUTATIONAL MATERIALS SCIENCE

Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic

(2007) İlker Bekir Topçu et al.   COMPUTATIONAL MATERIALS SCIENCE

Rice husk ash blended cement: Assessment of optimal level of replacement for strength and permeability properties of concrete

(2007) K. Ganesan et al.   CONSTRUCTION AND BUILDING MATERIALS