Optimization research on short-term load forecasting method for electric vehicles based on SSA-SVM

In order to improve the accuracy of short-term electric vehicle load forecasting, a combined forecasting model based on Sparrow Search Algorithm (SSA) and Support Vector Machine (SVM) is constructed. Using SVM model to predict electric vehicle load, accelerating the convergence speed of the prediction model through sparrow search algorithm, conducting global optimization in the solution space, expressing the impact of calculated parameters on the model through fitness, searching for the optimal model parameter data, and improving the overall accuracy of the prediction model. Through simulation experiments, comparing the prediction results of SVM models, and SSA-SVM shows better performance in electric vehicle load prediction.