Modeling and Sensitivity Analysis of Concrete Creep with Machine Learning Methods

Shear strength of steel fiber-unconfined reinforced concrete beam simulation: Application of novel intelligent model

(2019) Behrooz Keshtegar et al.   COMPOSITE STRUCTURES

Modeling the compressive strength of high-strength concrete: An extreme learning approach

(2019) Abobakr Khalil Al-Shamiri et al.   CONSTRUCTION AND BUILDING MATERIALS

Parametric sensitivity analysis and modelling of mechanical properties of normal- and high-strength recycled aggregate concrete using grey theory, multiple nonlinear regression and artificial neural networks

(2019) Jinjun Xu 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

Compressive strength prediction of recycled concrete based on deep learning

(2018) Fangming Deng 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

Particle Swarm Optimization Feature Selection for Breast Cancer Recurrence Prediction

(2018) Sapiah Binti Sakri et al.   IEEE Access

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

Deep neural network with high-order neuron for the prediction of foamed concrete strength

(2018) Tuan Nguyen et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE 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

Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

(2016) Jui-Sheng Chou et al.   APPLIED ENERGY

Genetic programming for experimental big data mining: A case study on concrete creep formulation

(2016) Amir H. Gandomi et al.   AUTOMATION IN CONSTRUCTION

McTwo: a two-step feature selection algorithm based on maximal information coefficient

(2016) Ruiquan Ge et al.   BMC BIOINFORMATICS

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

Predicting Compressive Strength of High-Performance Concrete Using Metaheuristic-Optimized Least Squares Support Vector Regression

(2016) Anh-Duc Pham 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

Creep of concrete at variable stresses and heating

(2015) Sergei Klovanych   Computers and Concrete

Optimization method, choice of form and uncertainty quantification of Model B4 using laboratory and multi-decade bridge databases

(2015) Roman Wendner et al.   MATERIALS AND STRUCTURES

Feature selection and analysis on correlated gas sensor data with recursive feature elimination

(2015) Ke Yan et al.   SENSORS AND ACTUATORS B-CHEMICAL

Prediction of concrete compressive strength: Research on hybrid models genetic based algorithms and ANFIS

(2013) Zhe Yuan et al.   ADVANCES IN ENGINEERING SOFTWARE

Tensile, compressive and flexural basic creep of concrete at different stress levels

(2013) Narintsoa Ranaivomanana et al.   CEMENT AND CONCRETE RESEARCH

Selection of Proper Neural Network Sizes and Architectures—A Comparative Study

(2012) David Hunter et al.   IEEE Transactions on Industrial Informatics

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

(2012) Sheng-En Fang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Prediction of shear strength of reinforced concrete beams using adaptive neuro-fuzzy inference system and artificial neural network

(2012) J. Amani et al.   Scientia Iranica

Fine tuning support vector machines for short-term wind speed forecasting

(2011) Junyi Zhou et al.   ENERGY CONVERSION AND MANAGEMENT

Global sensitivity analysis of unreinforced masonry structure using high dimensional model representation

(2011) D. Mukherjee et al.   ENGINEERING STRUCTURES

Model selection in finite element model updating using the Bayesian evidence statistic

(2011) Linda Mthembu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Detecting Novel Associations in Large Data Sets

(2011) D. N. Reshef et al.   SCIENCE

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

Variance decomposition and global sensitivity for structural systems

(2009) Sanjay R. Arwade et al.   ENGINEERING STRUCTURES

Chaotic particle swarm optimization algorithm in a support vector regression electric load forecasting model

(2008) Wei-Chiang Hong   ENERGY CONVERSION AND MANAGEMENT

Selecting of the optimal feature subset and kernel parameters in digital modulation classification by using hybrid genetic algorithm–support vector machines: HGASVM

(2007) Engin Avci   EXPERT SYSTEMS WITH APPLICATIONS