Application of PSO-Optimized Twin Support Vector Machine in Medium and Long-Term Load Forecasting under the Background of New Normal Economy

Abstract

In order to improve the accuracy of medium and long-term load forecasting in the new normal economy, this paper combines the PSO-optimized twin support vector machine to build a medium and long-term load forecasting model under the background of the new normal economy. Moreover, this paper uses the algorithm to debug the filter and studies the accurate prediction of the fine model by the progressive spatial mapping algorithm and the processing of the data by the vector fitting algorithm. In addition, this paper combines the PSO algorithm to optimize the twin support vector machine, constructs the optimized algorithm according to the flow chart, and applies it to the medium and long-term load forecasting under the background of a new normal economy. The experimental results verify that the PSO-optimized twin support vector machine has a very good application effect in medium and long-term load forecasting under the background of the new normal economy.