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

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

Design of neural network predictive controller based on imperialist competitive algorithm for automatic voltage regulator

(2019) M. Elsisi   NEURAL COMPUTING & APPLICATIONS

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

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

Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network

(2019) Hoang Nguyen et al.   Natural Resources Research

Prediction of Blast-induced Air Over-pressure in Open-Pit Mine: Assessment of Different Artificial Intelligence Techniques

(2019) Xuan-Nam Bui et al.   Natural Resources Research

A Comparative Assessment of Flood Susceptibility Modeling Using Multi-Criteria Decision-Making Analysis and Machine Learning Methods

(2019) Khabat Khosravi et al.   JOURNAL OF HYDROLOGY

Prediction of ultimate bearing capacity through various novel evolutionary and neural network models

(2019) Hossein Moayedi et al.   ENGINEERING WITH COMPUTERS

Developing an XGBoost model to predict blast-induced peak particle velocity in an open-pit mine: a case study

(2019) Hoang Nguyen et al.   Acta Geophysica

Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment

(2019) Hao Ling et al.   CONSTRUCTION AND BUILDING MATERIALS

Optimizing Levenberg–Marquardt backpropagation technique in predicting factor of safety of slopes after two-dimensional OptumG2 analysis

(2019) Xuan-Nam Bui et al.   ENGINEERING WITH COMPUTERS

Optimizing ANN models with PSO for predicting short building seismic response

(2019) Hoang Nguyen et al.   ENGINEERING WITH COMPUTERS

Optimizing an ANN model with genetic algorithm (GA) predicting load-settlement behaviours of eco-friendly raft-pile foundation (ERP) system

(2019) Longqi Liu et al.   ENGINEERING WITH COMPUTERS

Novel Soft Computing Model for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on Particle Swarm Optimization and XGBoost

(2019) Xiliang Zhang et al.   Natural Resources Research

Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns

(2019) Payam Sarir et al.   ENGINEERING WITH COMPUTERS

Feasibility of a novel predictive technique based on artificial neural network optimized with particle swarm optimization estimating pullout bearing capacity of helical piles

(2019) Bo Wang et al.   ENGINEERING WITH COMPUTERS

Freeze-thaw cycling damage evolution of additive cement mortar

(2019) Taoying Liu et al.   European Journal of Environmental and Civil Engineering

Determination of compound channel apparent shear stress: application of novel data mining models

(2019) Zohreh Sheikh Khozani et al.   JOURNAL OF HYDROINFORMATICS

Feasibility of Stochastic Gradient Boosting Approach for Evaluating Seismic Liquefaction Potential Based on SPT and CPT Case Histories

(2019) Jian Zhou et al.   JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES

Prediction of Surface Treatment Effects on the Tribological Performance of Tool Steels Using Artificial Neural Networks

(2019) Liborio Cavaleri et al.   Applied Sciences-Basel

A Comparative Study of PSO-ANN, GA-ANN, ICA-ANN, and ABC-ANN in Estimating the Heating Load of Buildings’ Energy Efficiency for Smart City Planning

(2019) Le Thi Le et al.   Applied Sciences-Basel

A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural Network

(2019) Yonghui Shang et al.   Natural Resources Research

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

Freeze-thaw damage evolution of fractured rock mass using nuclear magnetic resonance technology

(2019) Taoying Liu et al.   COLD REGIONS SCIENCE AND TECHNOLOGY

Concrete compressive strength using artificial neural networks

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

Prediction of Rock Size Distribution in Mine Bench Blasting Using a Novel Ant Colony Optimization-Based Boosted Regression Tree Technique

(2019) Shike Zhang et al.   Natural Resources Research

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model

(2018) Zaher Mundher Yaseen et al.   ADVANCES IN ENGINEERING SOFTWARE

A review of recycled aggregate in concrete applications (2000–2017)

(2018) Vivian W.Y. Tam et al.   CONSTRUCTION AND BUILDING MATERIALS

Compressive strength prediction of recycled concrete based on deep learning

(2018) Fangming Deng et al.   CONSTRUCTION AND BUILDING MATERIALS

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

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

Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution

(2018) Haoyuan Hong et al.   SCIENCE OF THE TOTAL ENVIRONMENT

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

A comparative study of artificial neural networks in predicting blast-induced air-blast overpressure at Deo Nai open-pit coal mine, Vietnam

(2018) Hoang Nguyen et al.   NEURAL COMPUTING & APPLICATIONS

Evaluation method of rockburst: State-of-the-art literature review

(2018) Jian Zhou et al.   TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY

Quantifying hourly suspended sediment load using data mining models: Case study of a glacierized Andean catchment in Chile

(2018) Khabat Khosravi et al.   JOURNAL OF HYDROLOGY

Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System

(2017) Gunasekaran Manogaran et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Self-compacting concrete strength prediction using surrogate models

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

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

(2017) Panagiotis Asteris et al.   SENSORS

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

Predicting of compressive strength of recycled aggregate concrete by genetic programming

(2016) Gholamreza Abdollahzadeh et al.   Computers and Concrete

Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran)

(2016) Iman Nasiri Aghdam et al.   Environmental Earth Sciences

Multiple linear regression, multi-layer perceptron network and adaptive neuro-fuzzy inference system for forecasting precipitation based on large-scale climate signals

(2016) Bahram Choubin et al.   HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES

Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods

(2016) Jian Zhou et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

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

A hybrid intelligent model combining ANN and imperialist competitive algorithm for prediction of corrosion rate in 3C steel under seawater environment

(2016) Amin Zadeh Shirazi et al.   NEURAL COMPUTING & APPLICATIONS

Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming

(2016) Palika Chopra et al.   Advances in Materials Science and Engineering

Predicting modulus elasticity of recycled aggregate concrete using M5′ model tree algorithm

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

Testing and analysis of axially loaded normal-strength recycled aggregate concrete filled steel tubular stub columns

(2015) Yuyin Wang et al.   ENGINEERING STRUCTURES

Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree

(2015) Dieu Tien Bui et al.   Landslides

Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks

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

A survey on the Imperialist Competitive Algorithm metaheuristic: Implementation in engineering domain and directions for future research

(2014) Seyedmohsen Hosseini et al.   APPLIED SOFT COMPUTING

The influence of the use of recycled aggregates on the compressive strength of concrete: a review

(2014) R.V. Silva et al.   European Journal of Environmental and Civil Engineering

Strength prediction model and methods for improving recycled aggregate concrete

(2013) Khaleel H. Younis et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of compressive strength of recycled aggregate concrete using artificial neural networks

(2012) Z.H. Duan 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

Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines

(2011) Jian Zhou et al.   SAFETY SCIENCE

Extreme learning machines: a survey

(2011) Guang-Bin Huang et al.   International Journal of Machine Learning and Cybernetics

Neural networks for predicting compressive strength of structural light weight concrete

(2009) Marai M. Alshihri et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models

(2009) Jafar Sobhani et al.   CONSTRUCTION AND BUILDING MATERIALS

An improved SVM method P‐SVM for classification of remotely sensed data

(2008) R. Zhang et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

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