An intelligent model for the prediction of the compressive strength of cementitious composites with ground granulated blast furnace slag based on ultrasonic pulse velocity measurements

Artificial neural networks for non-destructive identification of the interlayer bonding between repair overlay and concrete substrate

(2020) Sławomir Czarnecki et al.   ADVANCES IN ENGINEERING SOFTWARE

Experimental study on the engineering properties of alkali-activated GGBFS/FA concrete and constitutive models for performance prediction

(2020) Xinyu Cong et al.   CONSTRUCTION AND BUILDING MATERIALS

Estimation of the compressive strength of concretes containing ground granulated blast furnace slag using hybridized multi-objective ANN and salp swarm algorithm

(2020) Amirreza Kandiri et al.   CONSTRUCTION AND BUILDING MATERIALS

Efficient machine learning models for prediction of concrete strengths

(2020) Hoang Nguyen et al.   CONSTRUCTION AND BUILDING MATERIALS

Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete

(2019) Dong Dao et al.   Materials

The use of machine learning in boron-based geopolymers: Function approximation of compressive strength by ANN and GP

(2019) Ali Bagheri et al.   MEASUREMENT

Effect of perlite powder and silica fume on the compressive strength and microstructural characterization of self-compacting concrete with lime-cement binder

(2019) J. Esfandiari et al.   MEASUREMENT

Learned Prediction of Compressive Strength of GGBFS Concrete Using Hybrid Artificial Neural Network Models

(2019) In-Ji Han et al.   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

Determination of thermal damage in rock specimen using intelligent techniques

(2018) Nikhil Ninad Sirdesai et al.   ENGINEERING GEOLOGY

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

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

Determination of strength and modulus of elasticity of heterogenous sedimentary rocks: An ANFIS predictive technique

(2018) Ravi Kumar Umrao et al.   MEASUREMENT

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

The effect of failure to comply with technological and technical requirements on the condition of newly built cement mortar floors

(2018) Jerzy Hoła et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART L-JOURNAL OF MATERIALS-DESIGN AND APPLICATIONS

Prediction of soil compression coefficient for urban housing project using novel integration machine learning approach of swarm intelligence and Multi-layer Perceptron Neural Network

(2018) Dieu Tien Bui et al.   ADVANCED ENGINEERING INFORMATICS

Developing novel models using neural networks and fuzzy systems for the prediction of strength of rocks from key geomechanical properties

(2017) L.K. Sharma et al.   MEASUREMENT

Towards sustainable concrete

(2017) Paulo J. M. Monteiro et al.   NATURE MATERIALS

Development of novel methods to predict the strength properties of thermally treated sandstone using statistical and soft-computing approach

(2017) Nikhil Ninad Sirdesai et al.   NEURAL COMPUTING & APPLICATIONS

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

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

Creep and drying shrinkage of concrete containing GGBFS

(2016) M. Shariq et al.   CEMENT & CONCRETE COMPOSITES

Estimation of compressive strength of hollow concrete masonry prisms using artificial neural networks and adaptive neuro-fuzzy inference systems

(2016) Qiang Zhou et al.   CONSTRUCTION AND BUILDING MATERIALS

Evaluating the modulus of elasticity of soil using soft computing system

(2016) L. K. Sharma et al.   ENGINEERING WITH COMPUTERS

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

(2016) Md. Safiuddin et al.   Materials

Detecting the Presence of High Water-to-Cement Ratio in Concrete Surfaces Using Highly Nonlinear Solitary Waves

(2016) Piervincenzo Rizzo et al.   Applied Sciences-Basel

Principal Component Analysis combined with a Self Organization Feature Map to determine the pull-off adhesion between concrete layers

(2015) Łukasz Sadowski et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks

(2015) Mehdi Nikoo et al.   Advances in Materials Science and Engineering

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

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

Experimental analysis of properties of recycled coarse aggregate (RCA) concrete with mineral additives

(2014) Ö. Çakır   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

Earthquake performance of infilled frames using neural networks and experimental database

(2013) Tanja Kalman Šipoš et al.   ENGINEERING STRUCTURES

Determination of compressive strength of concrete using Self Organization Feature Map (SOFM)

(2013) Mehdi Nikoo et al.   ENGINEERING WITH COMPUTERS

Concrete compressive strength analysis using a combined classification and regression technique

(2012) Jui-Sheng Chou et al.   AUTOMATION IN CONSTRUCTION

High-performance Concrete Compressive Strength Prediction using Time-Weighted Evolutionary Fuzzy Support Vector Machines Inference Model

(2012) Min-Yuan Cheng et al.   AUTOMATION IN CONSTRUCTION

Studies in ultrasonic pulse velocity of concrete containing GGBFS

(2012) Mohd Shariq et al.   CONSTRUCTION AND BUILDING MATERIALS

Artificial neural network models for lot-sizing problem: a case study

(2012) Ercan Şenyiğit et al.   NEURAL COMPUTING & APPLICATIONS

Predicting properties of High Performance Concrete containing composite cementitious materials using Artificial Neural Networks

(2011) Mohammad Iqbal Khan   AUTOMATION IN CONSTRUCTION

Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network

(2011) U. Atici   EXPERT SYSTEMS WITH APPLICATIONS

Properties of concrete containing ground granulated blast furnace slag (GGBFS) at elevated temperatures

(2011) Rafat Siddique et al.   Journal of Advanced Research

Mechanical properties of reactive powder concrete containing high volumes of ground granulated blast furnace slag

(2010) Halit Yazıcı et al.   CEMENT & CONCRETE COMPOSITES

A comparison of model selection methods for compressive strength prediction of high-performance concrete using neural networks

(2010) Marek Słoński   COMPUTERS & STRUCTURES

Comparison of artificial neural network and fuzzy logic models for prediction of long-term compressive strength of silica fume concrete

(2009) Fatih Özcan et al.   ADVANCES IN ENGINEERING SOFTWARE

Analysis of durability of high performance concrete using artificial neural networks

(2008) R. Parichatprecha et al.   CONSTRUCTION AND BUILDING MATERIALS

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