Measurement and covariance analysis of 100Mo (n, 2n) 99Mo and 96Mo (n, p) 96Nb reaction cross sections at the incident neutron energy of 14.54 MeV

Ram, Sangeetha Prasanna; Nair, Jayakrishnan; Suryanarayana, S. V.; Danu, L. S.; Bishnoi, Saroj; Naik, H.; Ganesan, S.

doi:10.1007/s10967-020-07213-6

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…In this paper, the 96 Mo (n, p) 96 Nb reaction data has been considered, further to the experimental measurement of its cross section performed by the authors and reported in Ref. [2]. Niobium-96 is a radionuclide, having a half-life (T1/2) of about 23.35 hrs.…”

Section: Introductionmentioning

confidence: 99%

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Application of Machine Learning algorithms for experimental data processing and estimation of ⁹⁶Mo(n, p)⁹⁶Nb reaction cross section

Ram¹,

Nair²,

Singh³

et al. 2023

EPJ Web of Conf.

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In this paper, Machine learning techniques have been employed for preparation and estimation of 96 Mo (n, p) 96Nb reaction data. The experimental data of 96 Mo (n, p) 96Nb reaction available in the EXFOR database was retrieved, analyzed and processed using renormalization and data cleaning techniques. Estimation of the renormalized experimental data with outlier and without outlier, over the entire neutron energy range, was then performed using machine learning regression algorithms of Ordinary Least square, Ridge, Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Regressor. The results obtained were then compared and it was observed that the data preparation plays a significant role in data quality.

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Section: Introductionmentioning

confidence: 99%

“…Niobium-96 is a radionuclide, having a half-life (T1/2) of about 23.35 hrs. It finds extensive applications in the medical prosthetic field [2].…”

Section: Introductionmentioning

confidence: 99%

Application of Machine Learning algorithms for experimental data processing and estimation of ⁹⁶Mo(n, p)⁹⁶Nb reaction cross section

Ram¹,

Nair²,

Singh³

et al. 2023

EPJ Web of Conf.

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Application of Kalman filtering technique for evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction

Ram¹,

Nair²,

Suryanarayana

et al. 2021

Nuclear Instruments and Methods in Physics Research Section A:

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Evaluation of Neutron Cross-Section Data Using Gaussian Mixture Model and Digital Filter

Phatak,

Nair,

Prasanna Ram

et al. 2023

Nuclear Science and Engineering

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Measurement and covariance analysis of 100Mo (n, 2n) 99Mo and 96Mo (n, p) 96Nb reaction cross sections at the incident neutron energy of 14.54 MeV

Cited by 5 publications

References 18 publications

Application of Machine Learning algorithms for experimental data processing and estimation of ⁹⁶Mo(n, p)⁹⁶Nb reaction cross section

Application of Machine Learning algorithms for experimental data processing and estimation of ⁹⁶Mo(n, p)⁹⁶Nb reaction cross section

Application of Kalman filtering technique for evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction

Evaluation of Neutron Cross-Section Data Using Gaussian Mixture Model and Digital Filter

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Measurement and covariance analysis of 100Mo (n, 2n) 99Mo and 96Mo (n, p) 96Nb reaction cross sections at the incident neutron energy of 14.54 MeV

Cited by 5 publications

References 18 publications

Application of Machine Learning algorithms for experimental data processing and estimation of 96Mo(n, p)96Nb reaction cross section

Application of Machine Learning algorithms for experimental data processing and estimation of 96Mo(n, p)96Nb reaction cross section

Application of Kalman filtering technique for evaluation of neutron cross section data of 100Mo (n, 2n) 99Mo reaction

Evaluation of Neutron Cross-Section Data Using Gaussian Mixture Model and Digital Filter

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Product

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Application of Machine Learning algorithms for experimental data processing and estimation of ⁹⁶Mo(n, p)⁹⁶Nb reaction cross section

Application of Machine Learning algorithms for experimental data processing and estimation of ⁹⁶Mo(n, p)⁹⁶Nb reaction cross section