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 NOx-content are made using data collected from a 25 MW district heating thermal power plant
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