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- W133044733 abstract "Dynamic Data reconciliation (DDR) is the adjustment of a set of process data based on models of the process so that the derived estimates conform to natural laws. In this paper, a novel particle swarm optimization based on uncertain knowledge (PSO-UK) for DDR and outliers detection is proposed. The uncertain knowledge is introduced in particle swarm optimization (PSO) algorithm, which limited the search center and range of particles, making the particles fly toward the direction close to the optimal solution. So the confidence of particles is improved and the premature problem can be overcome. Simulation of a continuous stirred tank reactor (CSTR), verifies the effectiveness of the proposed algorithm." @default.
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- W133044733 date "2012-01-01" @default.
- W133044733 modified "2023-09-22" @default.
- W133044733 title "Particle Swarm Optimization Based on Uncertain Knowledge for Dynamic Data Reconciliation" @default.
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- W133044733 doi "https://doi.org/10.1007/978-3-642-28658-2_12" @default.
- W133044733 hasPublicationYear "2012" @default.
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