Regression analysis of experimental reaction cross-section data of 241Am(n, 2n)240 Am

Pre-processing of neutron reaction cross-section is essential in the nuclear data evaluation. This work aims to pre-process experimental cross-section data of (241) Am (n, 2n) (240) Am neutron reaction. Pre-processing of the experimental data includes re-normalization, removal of the outliers, integrating multiple cross-section values at single energy to single cross-section value, and regression on the cleaned experimental data. To remove outliers from the data, standardized residual and studentized residual have been used. For integration of multiple cross-section values to single cross-section value, the weighted average method has been used. Regression on the cleaned experimental data has been accomplished using the Gaussian Process Regression (GPR) and Polynomial Regression (PR), and the performance of both regression methods has been studied using statistical indices such as the determination of coefficient (R-2) and the sum of the square of residual (SSres).