The NOx and SOx output of a combined heat and power plant is studied with the aim of replacing the physical sensor array with a mathematical formula that can compute the emissions rather than measure them. The model is determined using machine learning from historical measurements and uses neural networks. As the model can be cheaply deployed, will not drift, and will not malfunction or fail, the model has significant added value over a physical sensor. We find that the accuracy of the model is comparable to the accuracy of the measurement and is thus suitable for a full replacement.

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