A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

Soft trees with neural components as image-processing technique for archeological excavations

(2020) Marcin Woźniak et al.   Personal and Ubiquitous Computing

A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model

(2020) Jin Duan et al.   ENGINEERING WITH COMPUTERS

Examining Hybrid and Single SVM Models with Different Kernels to Predict Rock Brittleness

(2020) Danial Jahed Armaghani et al.   Sustainability

On the Use of Neuro-Swarm System to Forecast the Pile Settlement

(2020) Danial Jahed Armaghani et al.   Applied Sciences-Basel

A Novel Intelligent ELM-BBO Technique for Predicting Distance of Mine Blasting-Induced Flyrock

(2020) Bhatawdekar Ramesh Murlidhar et al.   Natural Resources Research

Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models

(2020) Hai-Bang Ly et al.   NEURAL COMPUTING & APPLICATIONS

Mapping and holistic design of natural hydraulic lime mortars

(2020) Maria Apostolopoulou et al.   CEMENT AND CONCRETE RESEARCH

Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures

(2019) Panagiotis G. Asteris et al.   NEURAL COMPUTING & APPLICATIONS

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

(2019) Panagiotis G. Asteris et al.   Applied Sciences-Basel

Neuro-genetic, neuro-imperialism and genetic programing models in predicting ultimate bearing capacity of pile

(2019) Wusi Chen et al.   ENGINEERING WITH COMPUTERS

An Adaptive Neuro-Fuzzy Inference Model to Predict Punching Shear Strength of Flat Concrete Slabs

(2019) Mohammed Mashrei et al.   Applied Sciences-Basel

A new development of ANFIS–GMDH optimized by PSO to predict pile bearing capacity based on experimental datasets

(2019) Hooman Harandizadeh et al.   ENGINEERING WITH COMPUTERS

Supervised Machine Learning Techniques to the Prediction of Tunnel Boring Machine Penetration Rate

(2019) Hai Xu et al.   Applied Sciences-Basel

Slope stability prediction for circular mode failure using gradient boosting machine approach based on an updated database of case histories

(2019) Jian Zhou et al.   SAFETY SCIENCE

Concrete compressive strength using artificial neural networks

(2019) Panagiotis G. Asteris et al.   NEURAL COMPUTING & APPLICATIONS

Invasive Weed Optimization Technique-Based ANN to the Prediction of Rock Tensile Strength

(2019) Lei Huang et al.   Applied Sciences-Basel

Intelligent Home Systems for Ubiquitous User Support by Using Neural Networks and Rule-Based Approach

(2019) Marcin Wozniak et al.   IEEE Transactions on Industrial Informatics

Emerging artificial intelligence methods in structural engineering

(2018) Hadi Salehi et al.   ENGINEERING STRUCTURES

Krill herd algorithm-based neural network in structural seismic reliability evaluation

(2018) Panagiotis G. Asteris et al.   MECHANICS OF ADVANCED MATERIALS AND STRUCTURES

Prediction of compressive and flexural strengths of a modified zeolite additive mortar using artificial neural network

(2018) E.K. Onyari et al.   CONSTRUCTION AND BUILDING MATERIALS

Predicting sanitary landfill leachate generation in humid regions using ANFIS modeling

(2018) Taher Abunama et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Prediction of bearing capacity of thin-walled foundation: a simulation approach

(2017) Ehsan Momeni et al.   ENGINEERING WITH COMPUTERS

Combining an experimental study and ANFIS modeling to predict landfill leachate transport in underlying soil—a case study in north of Iran

(2017) D. Yousefi Kebria et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Nondestructive Concrete Strength Estimation based on Electro-Mechanical Impedance with Artificial Neural Network

(2017) Tae-Keun Oh et al.   Journal of Advanced Concrete Technology

Hybrid neuro-heuristic methodology for simulation and control of dynamic systems over time interval

(2017) Marcin Woźniak et al.   NEURAL NETWORKS

Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials

(2017) Panagiotis Asteris et al.   SENSORS

Predicting the strength properties of slurry infiltrated fibrous concrete using artificial neural network

(2017) T. Chandra Sekhara Reddy   Frontiers of Structural and Civil Engineering

Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive strength of concrete

(2017) Faezehossadat Khademi et al.   Frontiers of Structural and Civil Engineering

Prediction and modeling of mechanical properties in fiber reinforced self-compacting concrete using particle swarm optimization algorithm and artificial neural network

(2016) Hadi Mashhadban et al.   CONSTRUCTION AND BUILDING MATERIALS

A new model based on gene expression programming to estimate air flow in a single rock joint

(2016) Manoj Khandelwal et al.   Environmental Earth Sciences

Prediction of self-compacting concrete strength using artificial neural networks

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

Properties of pumice aggregate concretes at elevated temperatures and comparison with ANN models

(2016) İbrahim Türkmen et al.   FIRE AND MATERIALS

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

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

Rock strength estimation: a PSO-based BP approach

(2016) E. Tonnizam Mohamad et al.   NEURAL COMPUTING & APPLICATIONS

Application of adaptive neuro-fuzzy technique and regression models to predict the compressive strength of geopolymer composites

(2016) Mehrzad Mohabbi Yadollahi et al.   NEURAL COMPUTING & APPLICATIONS

Potential of adaptive neuro fuzzy inference system for evaluating the factors affecting steel-concrete composite beam's shear strength

(2016) M. Safa et al.   STEEL AND COMPOSITE STRUCTURES

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

(2016) Md. Safiuddin et al.   Materials

Neuro-fuzzy technique to predict air-overpressure induced by blasting

(2015) Danial Jahed Armaghani et al.   Arabian Journal of Geosciences

Prediction of debonding strength for masonry elements retrofitted with FRP composites using neuro fuzzy and neural network approaches

(2015) Iman Mansouri et al.   COMPOSITES PART B-ENGINEERING

Adaptive neuro fuzzy prediction of deflection and cracking behavior of NSM strengthened RC beams

(2015) Kh Mahfuz ud Darain et al.   CONSTRUCTION AND BUILDING MATERIALS

Application of Artificial Neural Network for Predicting Shaft and Tip Resistances of Concrete Piles

(2015) Ehsan Momeni et al.   Earth Sciences Research Journal

Comparative performance of six supervised learning methods for the development of models of hard rock pillar stability prediction

(2015) Jian Zhou et al.   NATURAL HAZARDS

Developing a hybrid PSO–ANN model for estimating the ultimate bearing capacity of rock-socketed piles

(2015) Danial Jahed Armaghani et al.   NEURAL COMPUTING & APPLICATIONS

Analysing the accuracy of pavement performance models in the short and long terms: GMDH and ANFIS methods

(2015) Hasan Ziari et al.   Road Materials and Pavement Design

Using an Artificial Neural Network to Predict Mix Compositions of Steel Fiber-Reinforced Concrete

(2014) Merve Açikgenç et al.   ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING

Prediction of the unconfined compressive strength of soft rocks: a PSO-based ANN approach

(2014) Edy Tonnizam Mohamad et al.   Bulletin of Engineering Geology and the Environment

Comparison of fly ash, silica fume and metakaolin from mechanical properties and durability performance of mortar mixtures view point

(2014) Ali Mardani-Aghabaglou et al.   CONSTRUCTION AND BUILDING MATERIALS

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

(2013) Mehdi Nikoo et al.   ENGINEERING WITH COMPUTERS

EVOLVING RBF NEURAL NETWORKS FOR ADAPTIVE SOFT-SENSOR DESIGN

(2013) ALEX ALEXANDRIDIS   International Journal of Neural Systems

Influence of metakaolin and silica fume on the heat of hydration and compressive strength development of mortar

(2011) El-Hadj Kadri et al.   APPLIED CLAY SCIENCE

Some applications of Adaptive Neuro-Fuzzy Inference System (ANFIS) in geotechnical engineering

(2011) Ali Firat Cabalar et al.   COMPUTERS AND GEOTECHNICS

Developing operating rules for reservoirs considering the water quality issues: Application of ANFIS-based surrogate models

(2010) Foad Soltani et al.   EXPERT SYSTEMS WITH APPLICATIONS

Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic

(2009) Mustafa Sarıdemir   ADVANCES IN ENGINEERING SOFTWARE

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

Estimation of current-induced scour depth around pile groups using neural network and adaptive neuro-fuzzy inference system

(2008) Mohammad Zounemat-Kermani et al.   APPLIED SOFT COMPUTING

Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks

(2008) Gregor Trtnik et al.   ULTRASONICS

Predicting the compressive strength of steel fiber added lightweight concrete using neural network

(2007) Fatih Altun 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

Prediction of elastic modulus of normal and high strength concrete by artificial neural networks

(2007) Fuat Demir   CONSTRUCTION AND BUILDING MATERIALS

Study on strength and corrosion performance for steel embedded in metakaolin blended concrete/mortar

(2006) Anand Kuber Parande et al.   CONSTRUCTION AND BUILDING MATERIALS