![]() Finally and furthermore, FWA is benchmarked against genetic algorithms and multiple linear regression, showing its superiority over those algorithms regarding precision with respect to MAE, MAPE, and MAP measures. ![]() FWA is tested on a set of experimentally obtained measurements optimizing various objective functions-MSE, RMSE, Theil-2, MAE, MAPE, MAP-with results exhibiting its potential in providing highly accurate and precise signature detection. In particular, FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, where non-zero coefficients express the detected signatures. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. The analysis of measured data plays a significant role in enhancing nuclear nonproliferation mainly by inferring the presence of patterns associated with special nuclear materials.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |