Adaptive Genetic Algorithm Optimization of BP Neural Networks for Complex Y-Ray Spectrum Analysis

This study aims to solve the difficult problem of complex y-ray spectrum analysis by exploring and innovating the spectrum solving methods to improve the analysis precision and accuracy. The study started with an extensive research on the existing spectral analysis methods, from which the BP neural network was selected as the core research object. In order to verify the practical application of BP neural network in y-ray spectrum analysis, an accuracy test based on experimental data is designed and implemented. Aiming at the difficulties of insufficient accuracy and easy to fall into local optimal solutions in complex y-ray spectrum analysis, a BP neural network method based on adaptive genetic algorithm optimization is proposed. By integrating the global search capability of genetic algorithm and the local optimization characteristics of BP neural network, the method effectively overcomes the defects of traditional BP network, which is slow in convergence and easy to fall into local optima. The method provides an efficient solution for the accurate resolution of high-overlap y-ray spectra, especially in the quantitative analysis of mixed nuclide samples.