Step 4. GM-GRA-DPC-PSOSVR combined forecasting. The forecasting results of individual models are as the inputs to PSOSVR for establishing nonlinear combination, and the whole procedure based on Step 1 to Step 4 is called GM-GRA-DPC-PSOSVR model. Step 5. Forecasting comparisons. In order to test the effectiveness of the forecasting models, this research introduces MAPE(Mean Absolute Percentage Error), MAE(Mean Absolute Error), MSE, and improvement rates to compares the forecasting ability of GM-GRA-DPC-PSOSVR with individual forecasting models.

这段话也没有发现任何语法错误。该段介绍了GM-GRA-DPC-PSOSVR模型的构建过程中的第四步和第五步，即使用PSOSVR建立个体模型的非线性组合，整个过程基于步骤1到步骤4被称为GM-GRA-DPC-PSOSVR模型。为了测试预测模型的有效性，该研究引入MAPE（平均绝对百分比误差）、MAE（平均绝对误差）、MSE和改进率来比较GM-GRA-DPC-PSOSVR与个体预测模型的预测能力。