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    Neutron spectrum unfolding using artificial neural network and modified least square method

    , Article Radiation Physics and Chemistry ; Volume 126 , 2016 , Pages 75-84 ; 0969806X (ISSN) Hosseini, S. A ; Sharif University of Technology
    Elsevier Ltd  2016
    Abstract
    In the present paper, neutron spectrum is reconstructed using the Artificial Neural Network (ANN) and Modified Least Square (MLSQR) methods. The detector's response (pulse height distribution) as a required data for unfolding of energy spectrum is calculated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). Unlike the usual methods that apply inversion procedures to unfold the energy spectrum from the Fredholm integral equation, the MLSQR method uses the direct procedure. Since liquid organic scintillators like NE-213 are well suited and routinely used for spectrometry of neutron sources, the neutron pulse height distribution is... 

    Energy spectra unfolding of fast neutron sources using the group method of data handling and decision tree algorithms

    , Article Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment ; Volume 851 , 2017 , Pages 5-9 ; 01689002 (ISSN) Hosseini, S. A ; Esmaili Paeen Afrakoti, I ; Sharif University of Technology
    Abstract
    Accurate unfolding of the energy spectrum of a neutron source gives important information about unknown neutron sources. The obtained information is useful in many areas like nuclear safeguards, nuclear nonproliferation, and homeland security. In the present study, the energy spectrum of a poly-energetic fast neutron source is reconstructed using the developed computational codes based on the Group Method of Data Handling (GMDH) and Decision Tree (DT) algorithms. The neutron pulse height distribution (neutron response function) in the considered NE-213 liquid organic scintillator has been simulated using the developed MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif... 

    Evaluation of a new neutron energy spectrum unfolding code based on an adaptive neuro-fuzzy inference system (ANFIS)

    , Article Journal of Radiation Research ; Volume 59, Issue 4 , 2018 , Pages 436-441 ; 04493060 (ISSN) Hosseini, S. A ; Esmaili Paeen Afrakoti, I ; Sharif University of Technology
    Oxford University Press  2018
    Abstract
    The purpose of the present study was to reconstruct the energy spectrum of a poly-energetic neutron source using an algorithm developed based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is a kind of artificial neural network based on the Takagi-Sugeno fuzzy inference system. The ANFIS algorithm uses the advantages of both fuzzy inference systems and artificial neural networks to improve the effectiveness of algorithms in various applications such as modeling, control and classification. The neutron pulse height distributions used as input data in the training procedure for the ANFIS algorithm were obtained from the simulations performed by MCNPX-ESUT computational code...