Computer Simulation Method for Data Trust Analysis Based on Average Deviation Algorithm

Abstract

The computer simulation trust evaluation enhances the performance of the simulation system and promotes the recognition of the simulation system, but this technology still faces the problem of low calculation accuracy.This research proposes a data trust analysis method based on the improved average deviation degree algorithm. First, the average deviation degree and data trust degree are analyzed, and then the average deviation degree algorithm model based on the improved SecRPSO is constructed. Finally, the performance verification and application analysis of the model are carried out. The research shows that the prediction model established based on SecRPSO optimization algorithm has better fitting degree with the real load curve, and has better prediction accuracy and is relatively stable; Comparing the absolute mean relative error (MAPE) of three different algorithms, the MAPE of the proposed model is generally small, and the trend of the predicted results is close to the actual value, and the error fluctuates within the allowable range of engineering applications; the data trust analysis method based on the average deviation algorithm can effectively calculate the expected threshold information of the data, and find out the tolerance threshold. Therefore, this method can be extended to various management data such as finance, finance, engineering, and environmental protection.