Evaluation of the Rheological Properties of SCC Using Hybrid Random Forest Methods

Junsong Wang

doi:10.56748/ejse.24791

Authors

Junsong Wang Wuhan Technical University; Wuhan, Hubei, 430000, China

DOI:

https://doi.org/10.56748/ejse.24791

Keywords:

self-compacting concrete, fly ash, rheological properties, CS, random forests

Abstract

It is understood from the literature that limited researches were focusing on predicting both new or toughened characteristics of self-compacting concrete (SCC). Therefore, using the optimized Random Forests (RF) approach, it is tried to create some schemes to anticipate the new and toughened characteristics of SCC. The RF method's determinative variables are optimized by artificial hummingbird optimization (AHA) and grey wolf optimization (GWO) methods. The L-box test, V-funnel test, slump flow, and compressive strength (CS) in the toughened stage are taken into account attributes of SCC in the new stage. Outcomes show strong promise in both training and testing, as well as approximation. It denotes good precision in the training and approximation processes since the relationship among the measured and anticipated SCC qualities from hybrid schemes is satisfactory. Outcomes from AHA-RF outperformed those from GWO-RF and the literature. Generally, the AHA-developed RF scheme serves better than others, demonstrating the AHA tactic's capacity to choose the best variables for the under-consideration technique.

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