Assessment of Soft Computing Techniques for the Prediction of Compressive Strength of Bacterial Concrete

In this investigation, the potential of M5P, Random Tree (RT), Reduced Error Pruning Tree (REP Tree), Random Forest (RF), and Support Vector Regression (SVR) techniques have been evaluated and compared with the multiple linear regression-based model (MLR) to be used for prediction of the compressive...

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Detalles Bibliográficos
Autores principales: Almohammed, Fadi, Sihag, Parveen, Sammen, Saad Sh., Ostrowski, Krzysztof Adam, Singh, Karan, Prasad, C. Venkata Siva Rama, Zajdel, Paulina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777621/
https://www.ncbi.nlm.nih.gov/pubmed/35057207
http://dx.doi.org/10.3390/ma15020489

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8777621/
https://www.ncbi.nlm.nih.gov/pubmed/35057207
http://dx.doi.org/10.3390/ma15020489

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