Data-driven theoretical characterization of β-decay spectra in radioisotope energy materials via artificial fish swarm optimized adaptive kernel density estimation

Introduction Accurate modeling of beta-decay energy spectra is essential for theoretical analysis and performance optimization in radioisotope energy conversion. Conventional parameterization methods may introduce fitting bias, while fixed-bandwidth KDE lacks local adaptability for asymmetric, multi-peak and long-tailed spectral distributions. Methods This study developed an Artificial Fish Swarm Algorithm-Adaptive Kernel Density Estimation (AFSA-AKDE) framework. After spectral data preprocessin