A Method for improving Data Quality of Large-scale Simulation

Data quality has always been a concern for both system developers and users, especially in recent years, the accuracy and reliability of data in the application of some large simulation systems are becoming more and more imporant. Based on the six-grade scale model, firstly this paper sets on an index hierarchy of data quality evaluation and its weights, in order to understand the comprehensive status of large-scale simulation system data quality, then based on pearl curve function establishes data fitting model, and from the curve which we got can be directly seen the relationship between funding strength and data quality. At last based on the fund allocation model of genetic algorithm, we can promot the continuous improvement of the data quality, and further improve credibility of the large-scale large simulation system.