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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.1
- 수록면
- 807 - 817 (11page)
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초록· 키워드
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Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiationinformation of ground surface, geochemistry measuring of the abundance of Potassium, Thorium andUranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field ofnuclear science and human life. The BroydeneFletchereGoldfarbeShanno (BFGS), with its advancednumerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs)provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered byANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect differentarchitectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRSoutputs. The selected approach among of various training methods, with its low iteration cost and nondiagonalscaling allocation is a new powerful algorithm for AGRS data due to its inherent stochasticproperties. Experiments were performed by different architectures and trainings, the selected schemeachieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximumperformance in compare with different types of optimization strategies and algorithms. The proposedmethod is capable to be implemented on a cost effective and minimum electronic equipment to presentits real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). Theadvanced adaptation properties and models of neural network, the training of stochastic process and itsimplementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome ofthe study shows this method increases the quality of curvature information of AGRS data while cost ofthe algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate modelfor Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems
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참고문헌 (14)
참고문헌 신청
International Atomic Energy Agency / 1991 / Airborne Gamma Ray Spectrometer Surveying
최희동 / 2018 / Basic characterization of uranium by high-resolution gamma spectroscopy / Nuclear Engineering and Technology 50(6):929~936
B. Minty / 1997 / Fundamentals of airborne gamma-ray spectrometry / AGSO J. Aust. Geol. Geophys 17(2):39~50
Seyed Abolfazl Hosseini / 2017 / Sensitivity Analysis of the Galerkin Finite Element Method Neutron Diffusion Solver to the Shape of the Elements / Nuclear Engineering and Technology 49(1):29~42
E. Nazemi / 2016 / Precise Void Fraction Measurement in Two-phase Flows Independent of the Flow Regime Using Gamma-ray Attenuation / Nuclear Engineering and Technology 48(1):64~71
최희동 / 2018 / Basic characterization of uranium by high-resolution gamma spectroscopy / Nuclear Engineering and Technology 50(6):929~936
B. Minty / 1997 / Fundamentals of airborne gamma-ray spectrometry / AGSO J. Aust. Geol. Geophys 17(2):39~50
Seyed Abolfazl Hosseini / 2017 / Sensitivity Analysis of the Galerkin Finite Element Method Neutron Diffusion Solver to the Shape of the Elements / Nuclear Engineering and Technology 49(1):29~42
E. Nazemi / 2016 / Precise Void Fraction Measurement in Two-phase Flows Independent of the Flow Regime Using Gamma-ray Attenuation / Nuclear Engineering and Technology 48(1):64~71
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