ArticleMaterials (Basel, Switzerland)2021
Predictive Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Artificial Intelligence Approaches: MLPNN, ANFIS, and GEP.
Article in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed.
- Innovative sustainable concrete with waste glass materials: an explainable machine learning for compressive strength prediction.Scientific reports · 2026Article
- Statistical and ANN Modeling of Corrosion Behavior of Austenitic Stainless Steels in Aqueous Environments.Materials (Basel, Switzerland) · 2025Article
- A New Mesoscopic Parameter Inverse Analysis Method of Hydraulic Concrete Based on the SVR-HGWO Intelligent Algorithm.Materials (Basel, Switzerland) · 2025Article
- Optimizing the utilization of Metakaolin in pre-cured geopolymer concrete using ensemble and symbolic regressions.Scientific reports · 2025Article
- Article
- Application of machine learning approach to estimate the solubility of some solid drugs in supercritical COScientific reports · 2025Article
- Evaluating the dynamic response and phase angle behavior of SBS-modified asphalt mixtures for enhanced pavement performance.Scientific reports · 2024Article
- Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete.Scientific reports · 2024Article
- Development of machine learning models for forecasting the strength of resilient modulus of subgrade soil: genetic and artificial neural network approaches.Scientific reports · 2024Article
- Comparative analysis of various machine learning algorithms to predict strength properties of sustainable green concrete containing waste foundry sand.Scientific reports · 2024Article
- Numerical and artificial intelligence based investigation on the development of design guidelines for pultruded GFRP RHS profiles subjected to web crippling.Scientific reports · 2024Article
- Eco-Transformation of construction: Harnessing machine learning and SHAP for crumb rubber concrete sustainability.Heliyon · 2024Article
- Mechanical Framework for Geopolymer Gels Construction: An Optimized LSTM Technique to Predict Compressive Strength of Fly Ash-Based Geopolymer Gels Concrete.Gels (Basel, Switzerland) · 2024Article
- Systematic literature review on the application of machine learning for the prediction of properties of different types of concrete.PeerJ. Computer science · 2024Article
- Splitting tensile strength prediction of Metakaolin concrete using machine learning techniques.Scientific reports · 2023Article
- Article
- An efficient machine learning approach for predicting concrete chloride resistance using a comprehensive dataset.Scientific reports · 2023Article
- Article
- Optimisation of Embodied Carbon and Compressive Strength in Low Carbon Concrete.Materials (Basel, Switzerland) · 2022Article
- In-Depth Analysis of Cement-Based Material Incorporating Metakaolin Using Individual and Ensemble Machine Learning Approaches.Materials (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Silica fume (SF) is a mineral additive that is widely used in the construction industry when producing sustainable concrete. The integration of SF in concrete as a partial replacement for cement has several evident benefits, including reduced CO
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.