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Regression and artificial neural network models for strength properties of engineered cementitious composites

https://doi.org/10.1007/s00521-016-2602-3
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1 of the 36 references listed on this page is in the Retraction Watch database as retracted (export 2026-10-21): 10.1016/j.engstruct.2015.03.070 (notice 2018-06-14).

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s11431-012-4990-7openalex-snapshot
Effect of composition on flexural behavior of engineered cementitious composites
inferredcites →https://doi.org/10.1016/j.advengsoft.2008.10.005openalex-snapshot
Fuzzy logic and statistical-based modelling of the Marshall Stability of asphalt concrete under varying temperatures and exposure times
inferredcites →https://doi.org/10.1016/j.cemconres.2004.03.028openalex-snapshot
Prediction of cement strength using soft computing techniques
inferredcites →https://doi.org/10.1016/j.conbuildmat.2011.10.051openalex-snapshot
Investigation of self-healing behavior of Engineered Cementitious Composites (ECC) materials
inferredcites →https://doi.org/10.1016/j.conbuildmat.2013.01.016openalex-snapshot
Modeling compressive strength of EPS lightweight concrete using regression, neural network and ANFIS
inferredcites →https://doi.org/10.1016/j.conbuildmat.2013.03.088openalex-snapshot
Development of green engineered cementitious composites using iron ore tailings as aggregates
inferredcites →https://doi.org/10.1016/j.conbuildmat.2013.07.104openalex-snapshot
Mechanical and thermal properties of green lightweight engineered cementitious composites
inferredcites →https://doi.org/10.1016/j.engstruct.2015.03.070openalex-snapshot
RETRACTED: Estimating unconfined compressive strength of cockle shell–cement–sand mixtures using soft computing methodologies
inferredcites →https://doi.org/10.1016/j.eswa.2010.11.018openalex-snapshot
Artificial neural network based modelling of the Marshall Stability of asphalt concrete
inferredcites →https://doi.org/10.1016/j.eswa.2011.08.087openalex-snapshot
Comparing the performance of neural networks developed by using Levenberg–Marquardt and Quasi-Newton with the gradient descent algorithm for modelling a multiple response grinding process
inferredcites →https://doi.org/10.1016/j.powtec.2015.02.045openalex-snapshot
Application of adaptive neuro-fuzzy technique to predict the unconfined compressive strength of PFA-sand-cement mixture
inferredcites →https://doi.org/10.1016/s0008-8846(03)00006-1openalex-snapshot
The use of GA–ANNs in the modelling of compressive strength of cement mortar
inferredcites →https://doi.org/10.1016/s0958-9465(02)00056-2openalex-snapshot
Constitutive rheological control to develop a self-consolidating engineered cementitious composite reinforced with hydrophilic poly(vinyl alcohol) fibers
inferredcites →https://doi.org/10.1061/(asce)0733-9445(2003)129:4(554)openalex-snapshot
Neural Network Modeling of Confined Compressive Strength and Strain of Circular Concrete Columns
inferredcites →https://doi.org/10.1061/(asce)0899-1561(1998)10:2(66)openalex-snapshot
INNOVATIONS FORUM : Engineered Cementitious Composites for Structural Applications
inferredcites →https://doi.org/10.1061/(asce)0899-1561(2006)18:3(462)openalex-snapshot
Prediction of Concrete Strength Using Neural-Expert System
inferredcites →https://doi.org/10.1061/(asce)mt.1943-5533.0000413openalex-snapshot
Using Neural Networks for Prediction of Properties of Polymer Concrete with Fly Ash
inferredcites →https://doi.org/10.1061/(asce)mt.1943-5533.0000985openalex-snapshot
Strength Prediction of High-Strength Concrete by Fuzzy Logic and Artificial Neural Networks
inferredcites →https://doi.org/10.1109/5.784219openalex-snapshot
Evolving artificial neural networks
inferredcites →https://doi.org/10.1175/1520-0477(1982)063<1309:scoteo>2.0.co;2openalex-snapshot
Some Comments on the Evaluation of Model Performance
inferredcites →https://doi.org/10.12989/cac.2006.3.1.001openalex-snapshot
ReliabIlity analysis of containment building subjected to earthquake load using response surface method
inferredcites →https://doi.org/10.12989/cac.2006.3.6.439openalex-snapshot
Artificial neural network model for the strength prediction of fully restrained RC slabs subjected to membrane action
inferredcites →https://doi.org/10.14359/12325openalex-snapshot
Interface Tailoring for Strain-Hardening Polyvinyl Alcohol-Engineered Cementitious Composite (PVA-ECC)
inferredcites →https://doi.org/10.14359/12958openalex-snapshot
Design of Engineered Cementitious Composite Suitable for Wet-Mixture Shotcreting
inferredcites →https://doi.org/10.14359/18668openalex-snapshot
Engineered Cementitious Composites with High-Volume Fly Ash
inferredcites →https://doi.org/10.14359/18966openalex-snapshot
Use of High Volumes of Fly Ash to Improve ECC Mechanical Properties and Material Greenness
inferredcites →https://doi.org/10.14359/19897openalex-snapshot
Large-Scale Processing of Engineered Cementitious Composites
inferredcites →https://doi.org/10.14359/51663759openalex-snapshot
Assessing Mechanical Properties and Microstructure of Fire-Damaged Engineered Cementitious Composites
inferredcites →https://doi.org/10.14359/51664049openalex-snapshot
Self-Healing Characterization of Engineered Cementitious Composite Materials
inferredcites →https://doi.org/10.14359/51664210openalex-snapshot
High-Early-Strength Engineered Cementitious Composites for Fast, Durable Concrete Repair—Material Properties
inferredcites →https://doi.org/10.14359/51684088openalex-snapshot
Investigation of Properties of Engineered Cementitious Composites Incorporating High Volumes of Fly Ash and Metakaolin
inferredcites →https://doi.org/10.14359/51684160openalex-snapshot
Combined Effect of Aggregate and Mineral Admixtures on Tensile Ductility of Engineered Cementitious Composites
inferredcites →https://doi.org/10.14359/56556openalex-snapshot
Influence of Aggregate Type and Size on Ductility and Mechanical Properties of Engineered Cementitious Composites
inferredcites →https://doi.org/10.14359/56656openalex-snapshot
Rheological Control in Production of Engineered Cementitious Composites
inferredcites →https://doi.org/10.3151/jact.1.215openalex-snapshot
On Engineered Cementitious Composites (ECC)
inferredcites →https://doi.org/10.3390/polym7071299openalex-snapshot
Structural Performance of Polymer Fiber Reinforced Engineered Cementitious Composites Subjected to Static and Fatigue Flexural Loading

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4054584openalex-extracted
Effect of Mineral Admixtures in Engineered Cementitious Composites Using Machine Learning Approach
inferred← citeshttps://doi.org/10.2139/ssrn.4161376openalex-extracted
inferred← citeshttps://doi.org/10.1002/adpr.202100052openalex-snapshot
Surface Plasmon Resonance of Gold Nano‐Sea‐Urchins Controlled by Machine‐Learning‐Based Regulation in Seed‐Mediated Growth
inferred← citeshttps://doi.org/10.1002/adpr.202170031openalex-snapshot
Surface Plasmon Resonance of Gold Nano‐Sea‐Urchins Controlled by Machine‐Learning‐Based Regulation in Seed‐Mediated Growth
inferred← citeshttps://doi.org/10.1002/eng2.12676openalex-snapshot
Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend
inferred← citeshttps://doi.org/10.1002/pc.29082openalex-snapshot
A review on recent applications of machine learning in mechanical properties of composites
inferred← citeshttps://doi.org/10.1002/suco.202400231openalex-snapshot
Prediction on mechanical properties of engineered cementitious composites: An experimental and machine learning approach
inferred← citeshttps://doi.org/10.1007/978-981-15-4530-6_3openalex-snapshot
Prediction of Engineering Parameters Based on Improved Artificial Neural Network
inferred← citeshttps://doi.org/10.1007/s00500-019-03833-7openalex-snapshot
Strength prediction of similar materials to ionic rare earth ores based on orthogonal test and back propagation neural network
inferred← citeshttps://doi.org/10.1007/s00521-020-04972-xopenalex-snapshot
Prediction of mechanical and penetrability properties of cement-stabilized clay exposed to sulfate attack by use of soft computing methods
inferred← citeshttps://doi.org/10.1007/s00521-023-08292-8openalex-snapshot
Evaluation of Dependency of Compression Index on Toughness Limit for Fine-Grained Soils
inferred← citeshttps://doi.org/10.1007/s10443-022-10061-0openalex-snapshot
Prediction of Equivalent Elastic Modulus for Metal-Coated Lattice Based on Machine Learning
inferred← citeshttps://doi.org/10.1007/s11831-021-09691-7openalex-snapshot
The Role of Artificial Neural Networks in Prediction of Mechanical and Tribological Properties of Composites—A Comprehensive Review
inferred← citeshttps://doi.org/10.1007/s12008-026-02670-xopenalex-snapshot
Computational analysis of polymer carbon nanotube composites using experiments and ANN modeling for manufacturing applications
inferred← citeshttps://doi.org/10.1007/s13726-025-01558-zopenalex-snapshot
Data-driven insights into the high-temperature behavior of polymer/carbon nanotubes nanocomposites
inferred← citeshttps://doi.org/10.1007/s41062-021-00675-xopenalex-snapshot
Unified model using artificial neural network for high strength fibrous concrete subjected to elevated temperature
inferred← citeshttps://doi.org/10.1007/s42107-022-00557-2openalex-snapshot
GA-based hybrid ANN optimization approach for the prediction of compressive strength of high-volume fly ash concrete mixes
inferred← citeshttps://doi.org/10.1007/s42452-025-07616-8openalex-snapshot
Review of machine learning approaches for predicting mechanical behavior of composite materials
inferred← citeshttps://doi.org/10.1007/s44242-024-00040-yopenalex-snapshot
Prediction of the mechanical performance of polyethylene fiber-based engineered cementitious composite (PE-ECC)
inferred← citeshttps://doi.org/10.1007/s44242-024-00042-wopenalex-snapshot
Revolutionizing engineered cementitious composite materials (ECC): the impact of XGBoost-SHAP analysis on polyvinyl alcohol (PVA) based ECC predictions
inferred← citeshttps://doi.org/10.1007/s44245-025-00134-2openalex-snapshot
Predictive modeling of thermoplastic nanocomposites using machine learning algorithms
inferred← citeshttps://doi.org/10.1016/j.cemconcomp.2025.106009openalex-snapshot
New opportunity: Materials genome strategy for engineered cementitious composites (ECC) design
inferred← citeshttps://doi.org/10.1016/j.compositesb.2023.110993openalex-snapshot
Generative AI for performance-based design of engineered cementitious composite
inferred← citeshttps://doi.org/10.1016/j.compstruct.2023.116815openalex-snapshot
Non-destructive strength prediction of composite laminates utilizing deep learning and the stochastic finite element methods
inferred← citeshttps://doi.org/10.1016/j.compstruct.2025.119906openalex-snapshot
Novel hybrid machine learning framework for high-fidelity prediction of fly ash-based geopolymer concrete strength
inferred← citeshttps://doi.org/10.1016/j.conbuildmat.2021.122807openalex-snapshot
An ensemble method for predicting the mechanical properties of strain hardening cementitious composites
inferred← citeshttps://doi.org/10.1016/j.conbuildmat.2022.127933openalex-snapshot
Prediction on compressive strength of Engineered Cementitious composites using Machine learning approach
inferred← citeshttps://doi.org/10.1016/j.cscm.2022.e00998openalex-snapshot
Predicting mechanical properties of engineering cementitious composite reinforced with PVA using artificial neural network
inferred← citeshttps://doi.org/10.1016/j.cscm.2023.e02172openalex-snapshot
Unveiling the potential of an evolutionary approach for accurate compressive strength prediction of engineered cementitious composites
inferred← citeshttps://doi.org/10.1016/j.dibe.2023.100285openalex-snapshot
Composition prediction of pore solution in hardened concrete materials based on machine learning
inferred← citeshttps://doi.org/10.1016/j.dibe.2024.100459openalex-snapshot
Performance prediction and analysis of engineered cementitious composites based on machine learning
inferred← citeshttps://doi.org/10.1016/j.dibe.2026.100963openalex-snapshot
Generative design of engineered cementitious composites via AdaIN-WGAN: A style-transfer-based approach for inverse mixture mapping
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.116093openalex-snapshot
Generative artificial intelligence for automation design of low-carbon high-ductility engineered cementitious composites
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122474openalex-snapshot
Prediction of compressive strength of nano-silica modified engineering cementitious composites exposed to high temperatures using hybrid deep learning models
inferred← citeshttps://doi.org/10.1016/j.ijfatigue.2020.106089openalex-snapshot
A novel approach based on the elastoplastic fatigue damage and machine learning models for life prediction of aerospace alloy parts fabricated by additive manufacturing
inferred← citeshttps://doi.org/10.1016/j.istruc.2020.02.028openalex-snapshot
Prediction model for compressive arch action capacity of RC frame structures under column removal scenario using gene expression programming
inferred← citeshttps://doi.org/10.1016/j.istruc.2025.110032openalex-snapshot
Machine learning to estimate the tensile strength of cementitious composites
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2025.112028openalex-snapshot
Explainable ensemble algorithms with grey wolf optimization for estimation of the tensile performance of polyethylene fiber-reinforced engineered cementitious composite
inferred← citeshttps://doi.org/10.1016/j.procs.2017.11.300openalex-snapshot
Intelligent classification system for concrete compressive strength
inferred← citeshttps://doi.org/10.1038/s41524-022-00810-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41598-025-08526-wopenalex-snapshot
Data-driven assessment of corrosion in reinforced concrete structures embedded in clay dominated soils
inferred← citeshttps://doi.org/10.1088/1757-899x/1205/1/012023openalex-snapshot
Fibre-reinforced cementitious composite: parameter identification using Ohno shear beam test
inferred← citeshttps://doi.org/10.1109/aicis.2018.00024openalex-snapshot
A Novel Artificial Neural Network Scheme for Modelling of Nonlinear Soil Stress-Strain Modulus Exponent
inferred← citeshttps://doi.org/10.1109/esmarta66764.2025.11131699openalex-snapshot
SHAP-Based Explainable Machine Learning Framework for Interpreting SHCC Mix Design Parameters
inferred← citeshttps://doi.org/10.1155/2019/3831813openalex-snapshot
An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions
inferred← citeshttps://doi.org/10.15240/tul/008/2023-2-002openalex-snapshot
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inferred← citeshttps://doi.org/10.17515/resm2020.222ma1013openalex-snapshot
Strength prediction of engineered cementitious composites with artificial neural networks
inferred← citeshttps://doi.org/10.17762/turcomat.v12i10.5759openalex-snapshot
Predictive study on Mechanical strength of Lightweight concrete using MRA and ANN
inferred← citeshttps://doi.org/10.3390/ma12172678openalex-snapshot
Prediction Model for Mechanical Properties of Lightweight Aggregate Concrete Using Artificial Neural Network
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Predicting Mechanical Properties of High-Performance Fiber-Reinforced Cementitious Composites by Integrating Micromechanics and Machine Learning
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