Prediction and sensitivity analysis of self compacting concrete slump flow by random forest algorithm

• DOI: 10.58845/jstt.utt.2022.en58
• Publication Date: 2023-02-06T02:22:04Z
• Authors: Raghvendra Kumar; Hai-Van Thi Mai

Self-compacting concrete (SCC) is a construction material with many advantages, including high performance and the capacity to self-compact without mechanical vibration. As result, SCC widely used in construction, especially at locations where structures are difficult construct. Filling ability one of three basic requirements that must be met when designing mix. The slump flow (SF) determine mixture's filling capacity. it critical estimate this number fast precisely. purpose study propose use random forest (RF) model predict SF assess effect input parameters on output parameters. constructed RF using dataset 507 experimental results collected, which biggest data collection compared previous studies subject. Additionally, 10-fold cross-validation approach improve model's prediction performance. assessment criteria for testing have values RMSE = 59.5664 mm, MAE 32.4483 R 0.8614, respectively. This result shows an effective tool predicting SCC.