연구동향 분석

A COMPARATIVE STUDY ON APPLICABILITY AND EFFICIENCY OF MACHINE LEARNING ALGORITHMS FOR MODELING GAMMA-RAY SHIELDING BEHAVIORS

Bayram Bilmez Ozan Toker Selçuk Alp Ersoy Oz Orhan _ Içelli 2022년

논문상세정보
인용/피인용
' A COMPARATIVE STUDY ON APPLICABILITY AND EFFICIENCY OF MACHINE LEARNING ALGORITHMS FOR MODELING GAMMA-RAY SHIELDING BEHAVIORS' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Artificial neural network
  • fuzzy logic
  • massattenuationcoefficient
  • non-linearregressionanalysis
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' A COMPARATIVE STUDY ON APPLICABILITY AND EFFICIENCY OF MACHINE LEARNING ALGORITHMS FOR MODELING GAMMA-RAY SHIELDING BEHAVIORS' 의 참고문헌

  • XCOM: Photon Cross Sections Database
  • Validation of MCNPX with Experimental Results of Mass Attenuation Coefficients for Cement, Gypsum and Mixture
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    J H Hubbell [2006]
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    I. Akkurt [2010]
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    H. Bethe [1934]
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  • Neural Networks for Pattern Recognition
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    S. Alp [2018]
  • Modeling of gamma ray energy-absorption buildup factors for thermoluminescent dosimetric materials using multilayer perceptron neural network : a comparative study
    N. Kucuk [2013]
  • MATLAB
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    F. H. Attix [2008]
  • How Neural Nets Work
  • Fuzzy sets
    L.A. Zadeh [1965]
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    G. Zhang [1998]
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    V. P. Singh [2015]
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    J. Hamilton [1973]
  • Clustering-Based TSK neuro-fuzzy model for function approximation with interpretable sub-models
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  • Application of artificial neural network in precise prediction of cement elements percentages based on the neutron activation analysis
    E. E. Zadeh [2016]
  • Application of artificial neural network for predicting the optimal mixture of radiation shielding concrete
  • A novel comprehensive utilization of vanadium slag/epoxy resin/antimony trioxide ternary composite as gamma ray shielding material by MCNP 6.2 and BXCOM
  • A neural network approach to fatigue life prediction