Related references
Note: Only part of the references are listed.Evaluation of mechanical properties of concretes containing coarse recycled concrete aggregates using multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), and least squares support vector regression (LSSVR) models
Aliakbar Gholampour et al.
NEURAL COMPUTING & APPLICATIONS (2020)
Predicting ultimate bond strength of corroded reinforcement and surrounding concrete using a metaheuristic optimized least squares support vector regression model
Nhat-Duc Hoang et al.
NEURAL COMPUTING & APPLICATIONS (2020)
Prediction of fresh and hardened properties of self-compacting concrete using support vector regression approach
Prasenjit Saha et al.
NEURAL COMPUTING & APPLICATIONS (2020)
Compressive strength of Foamed Cellular Lightweight Concrete simulation: New development of hybrid artificial intelligence model
Ali Ashrafian et al.
CONSTRUCTION AND BUILDING MATERIALS (2020)
Concrete compressive strength using artificial neural networks
Panagiotis G. Asteris et al.
NEURAL COMPUTING & APPLICATIONS (2020)
Prediction of mechanical and penetrability properties of cement-stabilized clay exposed to sulfate attack by use of soft computing methods
Alper Sezer et al.
NEURAL COMPUTING & APPLICATIONS (2020)
Effect of side chain length change of polycarboxylate-ether based high range water reducing admixture on properties of self-compacting concrete
Muhammet Gokhan Altun et al.
CONSTRUCTION AND BUILDING MATERIALS (2020)
Effect of the polycarboxylate based water reducing admixture structure on self-compacting concrete properties: Main chain length
Suleyman Ozen et al.
CONSTRUCTION AND BUILDING MATERIALS (2020)
Prediction model for optimized self-compacting concrete with fly ash using response surface method based on fuzzy classification
Sundari Selvaraj et al.
NEURAL COMPUTING & APPLICATIONS (2019)
Modeling of bentonite/sepiolite plastic concrete compressive strength using artificial neural network and support vector machine
Ali Reza Ghanizadeh et al.
FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING (2019)
Expansion prediction of alkali aggregate reactivity-affected concrete structures using a hybrid soft computing method
Yang Yu et al.
NEURAL COMPUTING & APPLICATIONS (2019)
Modeling the compressive strength of high-strength concrete: An extreme learning approach
Abobakr Khalil Al-Shamiri et al.
CONSTRUCTION AND BUILDING MATERIALS (2019)
Performance evaluation of multiple adaptive regression splines, teaching-learning based optimization and conventional regression techniques in predicting mechanical properties of impregnated wood
Sebahattin Tiryaki et al.
EUROPEAN JOURNAL OF WOOD AND WOOD PRODUCTS (2019)
Prediction of Mechanical Strength of Fiber Admixed Concrete Using Multiple Regression Analysis and Artificial Neural Network
S. Karthiyaini et al.
ADVANCES IN MATERIALS SCIENCE AND ENGINEERING (2019)
Modelling uniaxial compressive strength of lightweight self-compacting concrete using random forest regression
Junfei Zhang et al.
CONSTRUCTION AND BUILDING MATERIALS (2019)
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
Jinjun Xu et al.
CONSTRUCTION AND BUILDING MATERIALS (2019)
Soft computing based formulations for slump, compressive strength, and elastic modulus of bentonite plastic concrete
Amir Tavana Amlashi et al.
JOURNAL OF CLEANER PRODUCTION (2019)
River Stage Forecasting Using Multiple Additive Regression Trees
Jin-Cheng Fu et al.
WATER RESOURCES MANAGEMENT (2019)
Deep neural network with high-order neuron for the prediction of foamed concrete strength
Tuan Nguyen et al.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING (2019)
The Nature-Inspired Metaheuristic Method for Predicting the Creep Strain of Green Concrete Containing Ground Granulated Blast Furnace Slag
Lukasz Sadowski et al.
MATERIALS (2019)
Forecasting Daily Streamflow Discharges Using Various Neural Network Models and Training Algorithms
Sinan Nacar et al.
KSCE JOURNAL OF CIVIL ENGINEERING (2018)
M5′ and Mars Based Prediction Models for Properties of Self- Compacting Concrete Containing Fly Ash
Ali Kaveh et al.
PERIODICA POLYTECHNICA-CIVIL ENGINEERING (2018)
Predicting compressive strength of lightweight foamed concrete using extreme learning machine model
Zaher Mundher Yaseen et al.
ADVANCES IN ENGINEERING SOFTWARE (2018)
Prediction of compressive strength and ultrasonic pulse velocity of fiber reinforced concrete incorporating nano silica using heuristic regression methods
Ali Ashrafian et al.
CONSTRUCTION AND BUILDING MATERIALS (2018)
Effect of Cement C3A Content on Properties of Cementitious Systems Containing High-Range Water-Reducing Admixture
Ali Mardani-Aghabaglou et al.
JOURNAL OF MATERIALS IN CIVIL ENGINEERING (2017)
EFFECT OF CEMENT FINENESS ON PROPERTIES OF CEMENTITIOUS MATERIALS CONTAINING HIGH RANGE WATER REDUCING ADMIXTURE
Ali Mardani-Aghabaglou et al.
JOURNAL OF GREEN BUILDING (2017)
Effect of gypsum type on properties of cementitious materials containing high range water reducing admixture
Ali Mardani-Aghabaglou et al.
CEMENT & CONCRETE COMPOSITES (2016)
ESTIMATING STRENGTH OF RUBBERIZED CONCRETE USING EVOLUTIONARY MULTIVARIATE ADAPTIVE REGRESSION SPLINES
Min-Yuan Cheng et al.
JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT (2016)
Multivariate adaptive regression splines and neural network models for prediction of pile drivability
Wengang Zhang et al.
GEOSCIENCE FRONTIERS (2016)
Predicting alien herb invasion with machine learning models: biogeographical and life-history traits both matter
Leiyi Chen et al.
BIOLOGICAL INVASIONS (2015)
Modeling stream dissolved oxygen concentration using teaching-learning based optimization algorithm
Adem Bayram et al.
ENVIRONMENTAL EARTH SCIENCES (2015)
Prediction of compaction parameters of coarse grained soil using multivariate adaptive regression splines (MARS)
Sunil Khuntia et al.
INTERNATIONAL JOURNAL OF GEOTECHNICAL ENGINEERING (2015)
Prediction of concrete compressive strength: Research on hybrid models genetic based algorithms and ANFIS
Zhe Yuan et al.
ADVANCES IN ENGINEERING SOFTWARE (2014)
Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey
Ergun Uzlu et al.
ENERGY (2014)
Artificial neural network for estimation of harbor oscillation in a cargo harbor basin
Murat Kankal et al.
NEURAL COMPUTING & APPLICATIONS (2014)
Rheological behaviour of self-compacting micro-concrete
Burak Felekoglu
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES (2014)
Compatibility between polycarboxylate-based admixtures and blended-cement pastes
M. M. Alonso et al.
CEMENT & CONCRETE COMPOSITES (2013)
Optimisation of rheological parameters and mechanical properties of superplasticised cement grouts containing metakaolin and viscosity modifying admixture
M. Sonebi et al.
CONSTRUCTION AND BUILDING MATERIALS (2013)
Effect of different types of superplasticizer on fresh, rheological and strength properties of self-consolidating concrete
Ali Mardani-Aghabaglou et al.
CONSTRUCTION AND BUILDING MATERIALS (2013)
Multivariate Adaptive Regression Spline (Mars) for Prediction of Elastic Modulus of Jointed Rock Mass
Pijush Samui
GEOTECHNICAL AND GEOLOGICAL ENGINEERING (2013)
Influence of cement properties on new generation superplasticizers performance
Jacek Golaszewski
CONSTRUCTION AND BUILDING MATERIALS (2012)
Compatibility between superplasticizer admixtures and cements with mineral additions
Olga Burgos-Montes et al.
CONSTRUCTION AND BUILDING MATERIALS (2012)
Effects of superplasticizers on the carbonation resistance of C3S and C3A hydration products
Tingshu He et al.
CONSTRUCTION AND BUILDING MATERIALS (2012)
Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques
Jui-Sheng Chou et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2011)
Comparison of artificial neural network and fuzzy logic models for prediction of long-term compressive strength of silica fume concrete
Fatih Oezcan et al.
ADVANCES IN ENGINEERING SOFTWARE (2009)
Effect of molecular weight of sulfanilic acid-phenol-formaldehyde condensate on the properties of cementitious system
Xinping Ouyang et al.
CEMENT AND CONCRETE RESEARCH (2009)
Prediction of long-term effects of GGBFS on compressive strength of concrete by artificial neural networks and fuzzy logic
Mustafa Saridemir et al.
CONSTRUCTION AND BUILDING MATERIALS (2009)
Model evaluation guidelines for systematic quantification of accuracy in watershed simulations
D. N. Moriasi et al.
TRANSACTIONS OF THE ASABE (2007)
The use of chemical admixtures in concrete. Part 1: Admixture-cement compatibility
C Bedard et al.
JOURNAL OF PERFORMANCE OF CONSTRUCTED FACILITIES (2005)
Rheological behavior of fine and large particle suspensions
M Schatzmann et al.
JOURNAL OF HYDRAULIC ENGINEERING-ASCE (2003)
Multiple additive regression trees with application in epidemiology
JH Friedman et al.
STATISTICS IN MEDICINE (2003)
Interaction between ettringite and a polynaphthalene sulfonate superplasticizer in a cementitious paste
W Prince et al.
CEMENT AND CONCRETE RESEARCH (2002)
Greedy function approximation: A gradient boosting machine
JH Friedman
ANNALS OF STATISTICS (2001)
A simplified view on chemical effects perturbing the action of superplasticizers
RJ Flatt et al.
CEMENT AND CONCRETE RESEARCH (2001)
Compatibility of superplasticizers with cements different in composition
S Erdogdu
CEMENT AND CONCRETE RESEARCH (2000)
Share Paper
