Integrated approach to assessing strength in slag-based geopolymer mortars: experimental study and modeling with advanced techniques
Yazarlar (2)
Türkiye
Doç. Dr. Şinasi BİNGÖL
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
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| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Journal of Materials Science |
| Dergi ISSN | 0022-2461 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q2 |
| Makale Dili | İngilizce |
| Basım Tarihi | 04-2024 |
| Cilt No | 59 |
| Sayfalar | 7258 / 7272 |
| DOI Numarası | 10.1007/s10853-024-09645-x |
| Makale Linki | http://dx.doi.org/10.1007/s10853-024-09645-x |
| Özet |
| The study consists of two main parts. In the initial phase, a variety of slag-based geopolymer mortars with different activator concentrations were prepared. These mortars underwent curing in both water and air environments for periods of 3, 7, 28, and 90 days, after which their compressive strength was evaluated at the conclusion of each curing interval. The second phase of the study is dedicated to the development of innovative models for estimating the compressive strength based on the data gathered. To achieve this, a range of techniques including multi-gene genetic programming (MGGP), artificial neural networks (ANN), XGBoost, SVM-Gauss, long short-term memory (LSTM), and convolutional neural networks (CNN) were employed to formulate a model capable of estimating compressive strength accurately. The study made use of various performance evaluation metrics such as mean squared error (MSE … |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
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| Google Scholar | 3 |