Abstract
This paper introduces a new procedure for extracting signals and their time delays that contain the most information about the desired soft sensor output using information-theoretic subset selection and a genetic algorithm. This procedure can be used before the creation of a soft sensor, as it is only based on historic values of the signals. The algorithm is tested on real problems from the cement industry, i.e., how the input’s time delays affect the quality of the soft sensor estimation of cement fineness in a cement mill.
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