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- W2621286668 abstract "Abstract Artificial neural networks are studied from process engineer's point of yiew. In engineering problems, uses of neural networks can be found from modelling of non-linear systems. In on-line process modelling, the problem of measurement data that has a low information content cannot be ignored. An attempt to collect recursively an infonnationrich training data set is made using a self-organising feature map preceding a multi-layer perceptron artificial neural network. The combined configuration is introduced and a case study is presented, where models for the fluidized-bed combustor flue gas NO x -content are made using data collected from a 25 MW district heating thermal power plant" @default.
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- W2621286668 date "1995-12-01" @default.
- W2621286668 modified "2023-09-26" @default.
- W2621286668 title "On-Line Modelling Using Adaptive Training Prototypes with an Application to the Fluidized-Bed Combustion Process" @default.
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- W2621286668 doi "https://doi.org/10.1016/s1474-6670(17)44748-3" @default.
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