Prediction of High-Performance Concrete Strength Using a Hybrid Artificial Intelligence Approach

Abstract

This study introduces an improved artificial intelligence (AI) approach called intelligence optimized support vector regression (IO-SVR) for estimating the compressive strength of high-performance concrete (HPC). The nonlinear functional mapping between the HPC materials and compressive strength is conducted using the AI approach. A dataset with 1,030 HPC experimental tests is used to train and validate the prediction model. Depending on the results of the experiments, the forecast outcomes of the IO-SVR model are of a much higher quality compared to the outcomes of other AI approaches. Additionally, because of the high-quality learning capabilities, the IO-SVR is highly recommended for calculating HPC strength.