Article

Article title USAGE OF A NUMERICAL SIMULATION OF RADIATION TRANSPORT FOR SOLVING THE PROBLEM OF REMOTE DETECTION OF A GAMMA- RAY SOURCE WITH A GIVEN SPECTRUM
Authors A.M. Bakalyarov, V.G.Bondur, M.D. Karetnikov, V.I. Lebedev, V.A. Makarov, G.V. Muradyan, A.B. Murynin, G.V. Yakovlev
Section SECTION II. MATHEMATICAL MODELLING OF PHYSICAL PROCESSES
Month, Year 06, 2012 @en
Index UDC 004.93; 539.1.08
DOI
Abstract Within the framework of mathematical methods applied to pattern recognition, a procedure for detection of a gamma-ray source with a given spectrum was developed and verified. The procedure involves usage of learning neural networks for separation into two classes (background and effect plus background) of spectra, obtained by means of gamma-spectrometer. Verification was carried out by means of a numerical simulation of radiation transport with Monte-Carlo method. Real conditions of an experiment were simulated, a set of spectra was obtained that was used for learning of multilayer perseptron. Verification was carried out separately for background in order to obtain a probability for false alarm and separately for the source with background in order to estimate a probability for detection of that source.

Download PDF

Keywords Gamma-ray source; neural network; gamma-spectrometer; numerical simulation; Monte-Carlo method; perseptron learning; detection.
References 1. Соболь И.М. Метод Монте-Карло. – М.: Наука, 1985.
2. Ермаков С.М., Михайлов Г.А. Курс статистического моделирования. – М.: Наука, 1976.
3. Бондур В.Г., Макаров В.А., Мурынин А.Б. Дистанционный метод поиска минералов с использованием мобильного источника высокоэнергетических протонов // Известия вузов. Геодезия и аэрофотосъемка. – 2010. – № 3. – С. 57-62.
4. Бондур В.Г., Макаров В.А., Мурынин А.Б. Дистанционный поиск сложных минералов с использованием высокоэнергетических протонов // Известия вузов. Геодезия и аэрофотосъемка. – 2011. – № 1. – С. 73-80.
5. Журавлев Ю.И, Рязанов В.В., Сенько О.В. Распознавание. Математические методы. Программная система. Практические применения. – М.: Фазис, 2006.
6. Бакаляров А.М., Балыш А.Я., Беляев С.Т., Лебедев В.И. Использование искусственных нейронных сетей для разделения событий по форме импульса. Препринт НИЦ «Курчатовский институт» ИАЭ-6089/2. – М., 1998.
7. Bakalyarov A.M., Balysh A.Ya., Belyaev S.T., Lebedev V.I. and Zhukov S.V. Identification of single events in the HPGe detector: Comparison of various methods based on the analysis of
simulated pulse shapes. Hep-ex 0203017 2002.
8. GEANT3.21 Detector Description and Simulation Tool, Manual, CERN Program Library Long Writeup W5013.
9. Peterson C. et al., JETNET 3.0 – A Versatile Artificial Neural Network Package, 1993.

Comments are closed.