ORNL Resolved Resonance Covariance Generation for ENDF/B-VII.1

Leal, L.C.; Guber, K. H.; Wiarda, Dorothea; Arbanas, Goran; Derrien, H.; Sayer, R.O.; Larson, N. M.; Dunn, Michael E.

doi:10.1016/j.nds.2012.11.006

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…This can not be done with the Bayesian updating procedures implemented in e.g. SAMMY [2,16] and KALMAN [17,18]. In Ref.…”

Section: A Least-squares Fitmentioning

confidence: 99%

“…In addition, when covariance data are present in the resonance region, they mostly result in rather low uncertainties. For example, the capture cross sections of 37 Cl, 235 U, 238 U and 239 Pu are recommended in the ENDF/B-VII.1 library with uncertainties of 1% and lower [1,2]. Such uncertainty levels are below the accuracy that can be reached with the most up to date capture cross section measurement methods that are presently available [3].…”

Section: Introductionmentioning

confidence: 99%

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On the Methodology to Calculate the Covariance of Estimated Resonance Parameters

Becker

Kopecky

Schillebeeckx

2015

Nuclear Data Sheets

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“…This can not be done with the Bayesian updating procedures implemented in e.g. SAMMY [2,16] and KALMAN [17,18]. In Ref.…”

Section: A Least-squares Fitmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Methodology to Calculate the Covariance of Estimated Resonance Parameters

Becker

Kopecky

Schillebeeckx

2015

Nuclear Data Sheets

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“…The first step is to calculate the output of each layer of neurons by determining the initial weights and thresholds of the input samples. The second stage is Refers to returning the error result from the output layer to the previous layer to modify the threshold and weight [10]. These two processes always alternate until the results of network training converge.…”

Section: Theoretical Introduction Of Abc-bp Hybrid Algorithmmentioning

confidence: 99%

Kernel Data Evaluation System and Modeling Based on ABC-BP Hybrid Algorithm

Nie

2022

Frontiers in Artificial Intelligence and Applications

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With the rapid development of the Internet, the demand for high-quality nuclear data services continues to grow. As the main carrier of network traffic, data centers face huge challenges in network resource management. In order to optimize the performance indicators of network flow (such as delay, jitter and packet loss rate, etc.), it is necessary to study the core data evaluation system and modeling. Through the theoretical introduction of nuclear data evaluation system and modeling and ABC-BP hybrid algorithm, this paper analyzes from three aspects: comprehensive data evaluation, nuclear data network modeling, and data evaluation system construction. Based on the relevant theoretical research of ABC-BP hybrid algorithm Based on the analysis of the feasibility of the nuclear data evaluation system and modeling research based on the algorithm theory, the existing nuclear data evaluation system and modeling system in the relevant literature are deeply discussed and studied. Scientific and operable evaluation index system to conduct nuclear data evaluation system and modeling for the ecological development of my country’s government open data, so that it can truly understand its own system status. According to the existing problems of the system, reasonably coordinate and configure the relationship between the elements in the system, and finally realize the balanced, stable and efficient operation of the system.The final experimental results show that when the data fusion coefficients are 49.7, 31.6, 56.3, 73.9 and 60.5, the corresponding data compatibility degrees are 76.9%, 80.2%, 78.4%, 77.1% and 79.3%, respectively. And the compatibility of the nuclear data evaluation system is always maintained at the level of about 78%, indicating that the nuclear data evaluation system based on the ABC-BP hybrid algorithm has good feasibility in terms of data compatibility.

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