Univ. of Utah, Salt Lake City, UT (United States); Purdue Univ., West Lafayette, IN (United States). Applied Intelligent Systems Lab. School of Nuclear Engineering; CNEC/NC State
Purdue Univ., West Lafayette, IN (United States). Applied Intelligent Systems Lab. School of Nuclear Engineering
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. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. 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. 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. 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.
Alamaniotis, Miltiadis and Tsoukalas, Lefteri H.. "Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures." Critical Developments and Applications of Swarm Intelligence, vol. 2018, Dec. 2017. https://doi.org/10.4018/978-1-5225-5134-8.ch007
Alamaniotis, Miltiadis, & Tsoukalas, Lefteri H. (2017). Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures. Critical Developments and Applications of Swarm Intelligence, 2018. https://doi.org/10.4018/978-1-5225-5134-8.ch007
Alamaniotis, Miltiadis, and Tsoukalas, Lefteri H., "Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures," Critical Developments and Applications of Swarm Intelligence 2018 (2017), https://doi.org/10.4018/978-1-5225-5134-8.ch007
@article{osti_1440899,
author = {Alamaniotis, Miltiadis and Tsoukalas, Lefteri H.},
title = {Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures},
annote = {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. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. 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. 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. 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.},
doi = {10.4018/978-1-5225-5134-8.ch007},
url = {https://www.osti.gov/biblio/1440899},
journal = {Critical Developments and Applications of Swarm Intelligence},
issn = {ISSN 2327-0411},
volume = {2018},
place = {United States},
publisher = {IRMA International},
year = {2017},
month = {12}}
Purdue Univ., West Lafayette, IN (United States); Univ. of Utah, Salt Lake City, UT (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation (NA-20)
Grant/Contract Number:
NA0002576
OSTI ID:
1440899
Journal Information:
Critical Developments and Applications of Swarm Intelligence, Journal Name: Critical Developments and Applications of Swarm Intelligence Vol. 2018; ISSN 2327-0411
Mitchell, Dean J.; Sanger, Howard M.; Marlow, Keith W.
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