How do neural networks work?
Typically you configure a neural network (NN) application by feeding it with a lot of sample data that contains the inputs and corresponding outputs that you would normally expect in your process. Consider a pollution control system on an incinerator as an example. The engineers spend quite a while gathering sample data using very expensive measurement devices. This data includes readings of the gases being produced by the plant under different operating conditions. The data is then fed to the NN application, and over time it develops a model that matches the behavior of the actual plant. The engineers test the model until they are happy that the model accurately predicts what type of gasses will be produced from the appropriate set of simulated plant conditions. Then the expensive measuring devices are removed and replaced with a NN application that reads the actual plant parameters and continuously predicts the gases being produced. The engineer then controls his plant so that he run
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