Table of Contents
Future Internet, Volume 12, Issue 6 (June 2020) – 15 articles
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Cover Story (view full-size image) Soft sensors (SSs) are inferential models used in many industrial fields. They allow real-time [...] Read more. Soft sensors (SSs) are inferential models used in many industrial fields. They allow real-time estimation of hard-to-measure variables as a function of easy-to-measure variables obtained from on-line sensors. SSs are generally built from industries’ historical databases through data-driven approaches. A critical issue in SSs design concerns the selection of input variables, among those available in a candidate dataset, that can reach great numbers in an industrial environment. Such numbers of inputs would make the design computationally demanding and lead to poorly performing models. An input selection procedure is necessary. Most input selection approaches for SS design are addressed and classified in the paper, with their benefits and drawbacks outlined, to guide the designer through this step. View this paper.