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- W2214576758 abstract "Given observations of selected concentrations one wishes to determine unknown intensities and locations of the sources for a hazard. The concentration of the hazard is governed by a steady-state nonlinear diffusion–advection partial differential equation and the best fit of the data. The discretized version leads to a coupled nonlinear algebraic system and a nonlinear least squares problem. The coefficient matrix is a nonsingular M-matrix and is not symmetric. Iterative methods are compositions of nonnegative least squares and Picard/Newton methods, and a convergence proof is given. The singular values of the associated least squares matrix are important in the convergence proof, the sensitivity to the parameters of the model, and the location of the observation sites." @default.
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- W2214576758 date "2015-12-15" @default.
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- W2214576758 title "Nonlinear least squares algorithm for identification of hazards" @default.
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- W2214576758 doi "https://doi.org/10.1080/23311835.2015.1118219" @default.
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