针对再生混凝土抗压强度预测问题,提出了一种基于遗传算法优化支持向量机(GA-SVM)的抗压强度预测模型。利用遗传算法对SVM的参数进行优化,并得到优化的SVM预测模型。仿真试验结果表明:与BP神经网络和传统SVM的预测结果相比,基于遗传算法优化支持向量机模型的预测精度更高。 Aiming at the compressive strength prediction of recycled concrete, a compressive strength prediction model based on genetic algorithm optimized support vector machine (GA-SVM) is proposed. The genetic algorithm is used to optimize the SVM parameters and the optimal SVM prediction model is obtained. The simulation results show that compared with the BP neural network and the traditional SVM, the prediction accuracy of the SVM model based on genetic algorithm is higher.