NSR Query Results
Output year order : Descending NSR database version of April 11, 2024. Search: Author = Z.A.Wang Found 4 matches. 2022WA26 Phys.Rev. C 106, L021304 (2022) Z.A.Wang, J.C.Pei, Y.J.Chen, C.Y.Qiao, F.R.Xu, Z.G.Ge, N.C.Shu Bayesian approach to heterogeneous data fusion of imperfect fission yields for augmented evaluations NUCLEAR REACTIONS ^{238}U(n, F), E<20 MeV; analyzed experimental data; calculated cumulative fission yields of ^{99}Mo, ^{135}Xe, ^{140}Ba, ^{147}Nd fragments, independent fission yields. Bayesian neural networks (BNNs) algorithm for machine learning.
doi: 10.1103/PhysRevC.106.L021304
2021QI04 Phys.Rev. C 103, 034621 (2021) C.Y.Qiao, J.C.Pei, Z.A.Wang, Y.Qiang, Y.J.Chen, N.C.Shu, Z.G.Ge Bayesian evaluation of charge yields of fission fragments of ^{239}U NUCLEAR REACTIONS ^{232,233}Th, ^{239}Pu(n, F), E=14 MeV; ^{239}Pu, ^{244}Cm(n, F), E=0.5 MeV; ^{255}Fm(n, F), E=0.025 eV; analyzed one-layer and two-layer Bayesian neural network (BNN) learning results of charge yields taken from JENDL. ^{235}U(n, F), E=0.025 eV and 0.5, 14 MeV; predicted BNN fission charge yields. ^{238}U(n, F)^{239}U^{*}, E=0.5 MeV; calculated and evaluated BNN fission charge yields. Double-layered Bayesian neural network (BNN) to learn and predict charge yields of fission fragments; deduced better performance of double-layer network better than that of the single-layer network with same number of neurons. Comparison with experimental data.
doi: 10.1103/PhysRevC.103.034621
2021WA52 Phys.Rev. C 104, 064608 (2021) Optimizing multilayer Bayesian neural networks for evaluation of fission yields NUCLEAR REACTIONS ^{235}U(n, F), E=0.5, 3.6, 4.49, 14 MeV; ^{229}Th, ^{242}Pu(n, F), E=0.01 MeV; ^{234}U(n, F), E=14 MeV; ^{238}U(n, F), E=0.5 MeV; analyzed and evaluated experimental data for induced fission yields using multilayer Bayesian neural networks (BNN) techniques with learning performances using different activation functions such as sine, tanh, sigmoid, and ReLU to improve their performance for evaluations of fission yields. ^{238}U(n, F)^{239}U^{*}; evaluated fission yields of compound nucleus with experimental data taken from GEF and ENDF libraries using double-layer BNN evaluations without and with penalty on negative values.
doi: 10.1103/PhysRevC.104.064608
2019WA26 Phys.Rev.Lett. 123, 122501 (2019) Z.-A.Wang, J.Pei, Y.Liu, Y.Qiang Bayesian Evaluation of Incomplete Fission Yields NUCLEAR REACTIONS ^{227,229,232}Th, ^{231}Pa, ^{232,233,234,235,236,237,238}U, ^{237,238}Np, ^{238,239,240,241,242}Pu, ^{241,243}Am, ^{242,243,244,245,246,248}Cm, ^{249,251}Cf, ^{254}Es, ^{255}Fm(n, F), E not given; analyzed available data using from JENDL library; deduced missing fission yield values using the Bayesian neural network (BNN) approach.
doi: 10.1103/PhysRevLett.123.122501
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