Improving Active Radon Data Modeling Using a Hybrid Method that Combines Neville Interpolation with Graph Method Using the BFGS Algorithm

Abstract

: This study presents new methods for improving modeling based on two methods: Neville's method and Graph method, using a shrinkage fusion method with weights calculated using the BFGS algorithm. To evaluate the performance of the Hybrid method and the basic methods in modeling, data on active radioactive radon gas were used in a number of selected areas of Baghdad. The importance of the study lies in improving the accuracy of modeling radon data, which is a hazardous gas with a radioactive effect, as traditional numerical methods may not provide sufficient accuracy in all cases. The results showed that Hybrid method outperformed the two separate methods, achieving the lowest sum of square errors (0.00353) compared to Neville's method (0.001432) and the Graph method (0.036126). the analysis also confirmed that the optimal combination of the two methods using calculated weights reduces deviations and improves the reliability of the results, making this method ideal for practical applications in monitoring active radioactive pollutants.