Prediction of sustainable concrete utilizing rice husk ash (RHA) as supplementary cementitious material (SCM): Optimization and hyper-tuning

Basalt fiber-reinforced foam concrete containing silica fume: An experimental study

(2022) Osman Gencel et al.   CONSTRUCTION AND BUILDING MATERIALS

New prediction models for the compressive strength and dry-thermal conductivity of bio-composites using novel machine learning algorithms

(2022) Mohsin Ali Khan et al.   Journal of Cleaner Production

Recycling of palm oil fuel ash and rice husk ash in the cleaner production of concrete

(2022) Kumar Gedela Santhosh et al.   Journal of Cleaner Production

Mapping Research Knowledge on Rice Husk Ash Application in Concrete: A Scientometric Review

(2022) Muhammad Nasir Amin et al.   Materials

Forecasting the Mechanical Properties of Plastic Concrete Employing Experimental Data Using Machine Learning Algorithms: DT, MLPNN, SVM, and RF

(2022) Afnan Nafees et al.   Polymers

Support vector regression (SVR) and grey wolf optimization (GWO) to predict the compressive strength of GGBFS-based geopolymer concrete

(2022) Hemn Unis Ahmed et al.   NEURAL COMPUTING & APPLICATIONS

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

Prediction of Catenary Action Capacity of RC Beam-Column Substructures under a Missing Column Scenario Using Evolutionary Algorithm

(2021) Iftikhar Azim et al.   KSCE Journal of Civil Engineering

Double-Target Based Neural Networks in Predicting Energy Consumption in Residential Buildings

(2021) Hossein Moayedi et al.   Energies

A water cycle-based error minimization technique in predicting the bearing capacity of shallow foundation

(2021) Hossein Moayedi et al.   ENGINEERING WITH COMPUTERS

Detection and prediction of lake degradation using landscape metrics and remote sensing dataset

(2021) Ali Azareh et al.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Prediction of Compressive Strength of Fly Ash Based Concrete Using Individual and Ensemble Algorithm

(2021) Ayaz Ahmad et al.   Materials

Comparative Study of Supervised Machine Learning Algorithms for Predicting the Compressive Strength of Concrete at High Temperature

(2021) Ayaz Ahmad 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

Predictive Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Artificial Intelligence Approaches: MLPNN, ANFIS, and GEP

(2021) Afnan Nafees et al.   Materials

Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Machine Learning Techniques

(2021) Afnan Nafees et al.   Polymers

Durability evaluation of GFRP rebars in harsh alkaline environment using optimized tree-based random forest model

(2021) Mudassir Iqbal et al.   Journal of Ocean Engineering and Science

Sustainable use of rice husk ash in cement-based materials: Environmental evaluation and performance improvement

(2020) Lingling Hu et al.   JOURNAL OF CLEANER PRODUCTION

Prediction of Hydropower Generation Using Grey Wolf Optimization Adaptive Neuro-Fuzzy Inference System

(2019) Majid Dehghani et al.   Energies

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

An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines

(2018) Bahram Choubin et al.   SCIENCE OF THE TOTAL ENVIRONMENT

A comparative study on the compressive strength prediction models for High Performance Concrete containing nano silica and copper slag using regression analysis and Artificial Neural Networks

(2016) S. Chithra et al.   CONSTRUCTION AND BUILDING MATERIALS

Comparative life cycle assessment of reactive MgO and Portland cement production

(2016) S. Ruan et al.   JOURNAL OF CLEANER PRODUCTION

Comparison of Data Mining Techniques for Predicting Compressive Strength of Environmentally Friendly Concrete

(2016) Behzad Abounia Omran et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Strength, permeability and microstructure of self-compacting concrete containing rice husk ash

(2015) Divya Chopra et al.   BIOSYSTEMS ENGINEERING

RETRACTED: Estimating unconfined compressive strength of cockle shell–cement–sand mixtures using soft computing methodologies

(2015) Shervin Motamedi et al.   ENGINEERING STRUCTURES

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

Damage prediction for regular reinforced concrete buildings using the decision tree algorithm

(2013) A. Karbassi et al.   COMPUTERS & STRUCTURES

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

Effect of off-white rice husk ash on strength, porosity, conductivity and corrosion resistance of white concrete

(2012) Rossella M. Ferraro et al.   CONSTRUCTION AND BUILDING MATERIALS

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

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

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

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

Assessment of the effects of rice husk ash particle size on strength, water permeability and workability of binary blended concrete

(2010) Alireza Naji Givi et al.   CONSTRUCTION AND BUILDING MATERIALS

Modeling of some properties of the crushed tile concretes exposed to elevated temperatures

(2010) Abdullah Demir et al.   CONSTRUCTION AND BUILDING MATERIALS

Concrete incorporating rice-husk ash without processing

(2010) R. Zerbino et al.   CONSTRUCTION AND BUILDING MATERIALS

Approximate Confidence and Prediction Intervals for Least Squares Support Vector Regression

(2010) Kris De Brabanter et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS

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

The use of linear regression methods and Pearson’s correlation matrix to identify mechanical–physical–chemical parameters controlling the micro-electrochemical behaviour of machined copper

(2008) J. Gravier et al.   CORROSION SCIENCE