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Extracting Knowledge and Computable Models from Data- Needs, Expectations, and Experience (2008)

Abstract
Abstract In modern industrial manufacturing, a great amount of data is gathered to monitor and analyze a given production process. Intelligent analysis of such data helps to reveal as much information about the production process as possible. This information is most useful if it is available in the form of interpretable and predictive models. Such models can be generated from data by means of (fuzzy logic based) machine learning methods. In this contribution we will describe industrial applications in the areas of process optimization and quality control where we have successfully established machine-learning methods as intelligent data analysis tools. 1

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Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=?doi=10.1.1.128.1790
Source http://www.unisoftwareplus.com/download/mlf_experiences.pdf
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Type text
Language English