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Updated: May 26, 2026

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems
Published on: July 30, 2019
Data-driven theoretical characterization of β-decay spectra in radioisotope energy materials via artificial fish
Yichen Ma1, Changlong Cai1,2, Huachen Liu1
1School of Optoelectronic Engineering, Xi'an Technological University, Xi'an, China.
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 preprocessing, RMSE was used as the fitness function, the bandwidth was reformulated as an adaptive coefficient-controlled structure, and AFSA was used to optimize key parameters through foraging, swarming and following behaviors.
Results:
The method was validated using Ni-63, S-35 and C-14 samples with different thicknesses. For a 2 um Ni-63 sample, AFSA-AKDE achieved MAE = 0.0116%, RMSE = 0.0156% and R2 = 0.9998792. For a 0.2 um C-14 sample, it achieved MAE = 0.0158%, RMSE = 0.0243% and R2 = 0.996687.
Discussion:
Compared with fixed-bandwidth KDE, normal distribution models and recent adaptive KDE variants, AFSA-AKDE provides improved accuracy, stability and local adaptability for reconstructing complex beta-decay energy distributions.
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