volume 231, issue 2, P199-210 2004
DOI: 10.1016/j.nucengdes.2004.02.007
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Abstract: Least squares problems occur frequently in nuclear science including the parameter identification of linear/nonlinear dynamic models, modeling the responses of the spatially distributed detectors, nuclear data treatment, response surface modeling of the thermal margin estimation, etc. Considering the inevitable measurement noise and transport kernel simplification, the ill-posedness of the least squares method can arise and limit the applicability of the assumed model structures. In this paper, a constructive…

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