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- W4323786135 abstract "In this study we consider dewatering sludge problem that appears in different industries and has both serious ecological and economic effect. Dewatering performance depends on real time water analysis content, which can be provided by the nuclear magnetic resonance sensors. These sensors produce the signal in a form of linear combinations of exponential functions with different amplitudes and relaxation time parameters, which represents the water exact content and volume of its components. We discuss different approaches on solving the water content analysis problem based on magnetic resonance sensors output and currently focus on solving the reduced optimization problem. We investigate the parameter fitting problem, discover its relation to content analysis problem. We examine influence of algorithm parameters and adding penalties to optimization criteria on approach performance. In this study we numerically prove the relation between the solution of the reduced optimization problem and water content analysis parameter identification." @default.
- W4323786135 created "2023-03-11" @default.
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- W4323786135 date "2023-01-01" @default.
- W4323786135 modified "2023-09-26" @default.
- W4323786135 title "Penalties and computational resources in NMR water content analysis parameter identification with differential evolution" @default.
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- W4323786135 doi "https://doi.org/10.1063/5.0125459" @default.
- W4323786135 hasPublicationYear "2023" @default.
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