ArticleScientific reports2023
Soft computing techniques for predicting the properties of raw rice husk concrete bricks using regression-based machine learning approaches.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed, 30 citations in OpenAlex.
- Optimization of concrete with human hair using experimental study and artificial neural network via response surface methodology and ANOVA.Scientific reports · 2025Article
- Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete.Scientific reports · 2024Article
- Mechanical properties optimization and cost analysis of agricultural waste as an alternative in brick production.Scientific reports · 2024Article
- Optimization and prediction of paver block properties with ceramic waste as fine aggregate using response surface methodology.Scientific reports · 2024Article
- Optimization of cassava peel ash concrete using central composite design method.Scientific reports · 2024Article
- Machine learning optimization of bio-sandcrete brick modelling using response surface methodology.Scientific reports · 2024Article
- Effects of aggregate sizes on the performance of laterized concrete.Scientific reports · 2024Article
- A study on waste PCB fibres reinforced concrete with and without silica fume made from electronic waste.Scientific reports · 2023Article
- A critical review of rheological models in self-compacting concrete for sustainable structures.Scientific reports · 2023Article
- Experimental investigation and modelling of the mechanical properties of palm oil fuel ash concrete using Scheffe's method.Scientific reports · 2023Article
- Recycling and sustainable applications of waste printed circuit board in concrete application and validation using response surface methodology.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, the replacement of raw rice husk, fly ash, and hydrated lime for fine aggregate and cement was evaluated in making raw rice husk-concrete brick. This study optimizes compressive strength, water absorption, and dry density of concrete brick containing recycled aggregates via Response Surface Methodology. The optimized model's accuracy is validated through Artificial Neural Network and Multiple Linear Regression. The Artificial Neural Network model captured the 100 data's variability from RSM optimization as indicated by the high R threshold- (R > 0.9997), (R > 0.99993), (R > 0.99997). Multiple Linear Regression model captured the data's variability the decent R
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.