Application of Intelligent Algorithm to Ill-Conditioned Matrix Correction in RFM Location Solution

The purpose of this study is to explore the application of intelligent algorithm to the ill-conditioned matrix correction in RFM (rotational feedback mechanism) positioning solution. By using intelligent algorithm, fault diagnosis, process monitoring and matrix optimization, an innovative RFM location solution system is proposed to improve the accuracy and reliability of location solution. Intelligent algorithm is used to learn the data in RFM positioning solution through training model, so as to realize the effective correction of ill-conditioned matrix and improve the positioning accuracy. By analyzing the data of RFM location solution, the fault diagnosis method is used to realize the early detection and diagnosis. Process monitoring operation data of RFM positioning solution to realize real-time monitoring of positioning solution process. Finally, the ill-conditioned matrix is corrected by using matrix optimization method, which provides an effective solution for RFM localization.