Traditional concrete currently struggles to meet the demands of the construction industry. To address this issue, oil palm shell aggregate green concrete has been developed. Raw materials for preparing oil palm shell aggregate green concrete were selected, and under the guidance of appropriate material mix ratios and preparation processes, five different samples of oil palm shell aggregate green concrete were ultimately produced. The DEGWO combined optimization algorithm was used to optimize the least squares support vector regression model, resulting in a DE-GWO-LSSVR-based performance prediction model for oil palm shell aggregate green concrete. This model was then applied to conduct predictive empirical analysis of the performance characteristics of oil palm shell aggregate green concrete. The predictive empirical analysis revealed that the actual compressive strength test values of the 14-day samples were distributed within the range of [60.42 MPa, 62.72 MPa], with an error of less than 1 MPa compared to the target results [60.36 MPa, 63.33 MPa], which is within an acceptable range. This demonstrates the application value of the DE-GWO-LSSVR model in oil palm shell aggregate green concrete.
