Article detail · 2021
Artificial neural network model to predict the compressive strength of eco-friendly geopolymer concrete incorporating silica fume and natural zeolite
YÖKSİS
OpenAlex
SJR Q1
JCR Q1
Citations 351
Top 1%
Percentile 99.9%
FWCI 25.7
- Year
- 2021
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue Journal of Cleaner Production
- Catalog match (ISSN) Journal of Cleaner Production
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
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Topics
Citations
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351 citations
OpenAlex cited_by_count (cache / database)
68 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Use of Waste Glass Powder toward more Sustainable Geopolymer Concrete 2023
- The prediction analysis of compressive strength and electrical resistivity of environmentally friendly concrete incorporating natural zeolite using artificial neural network 2022
- Influence of micro Fe2O3 and MgO on the physical and mechanical properties of the zeolite and kaolin based geopolymer mortar 2022
- Influence of micro Fe2O3 and MgO on the physical and mechanical properties of the zeolite and kaolin based geopolymer mortar 2022
- Influence of micro Fe2O3 and MgO on the physical and mechanical properties of the zeolite and kaolin based geopolymer mortar 2022
- A holistic assessment of the use of emerging recycled concrete aggregates after a destructive earthquake: Mechanical, economic and environmental 2022
- The effect of micro-SiO2 and micro-Al2O3 additive on the strength properties of ceramic powder-based geopolymer pastes 2022
- Comparison of different machine learning methods for estimating compressive strength of mortars 2022
- Comparison of different machine learning methods for estimating compressive strength of mortars 2022
- Comparison of different machine learning methods for estimating compressive strength of mortars 2022