Decision analytics and soft computing with industrial partners: A personal retrospective

József Mezei*, Matteo Brunelli

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


Methods in decision analytics are becoming essential tools for organizations to process the increasing amount of collected data. At the same time, these models should be capable of representing and utilizing the tacit knowledge of experts. In other words, companies require methods that can make use of imprecise information to deliver insights in real time. In this chapter, we provide a summary of three closely related research projects designed by building on the concept of knowledge mobilization. In these three cases, we provide solutions for typical business analytical problems originating mainly form the process industry. Fuzzy ontology represented as a fuzzy relation provides the basis for every application. By looking at the similarities among the three cases, we discuss the main lessons learnt and pro-vide some important factors to be considered in future applications of soft computing in industrial applications.

Original languageEnglish
Title of host publicationFuzzy Technology
Subtitle of host publicationPresent Applications and Future Challenges
EditorsMikael Collan, Mario Fedrizzi, Janusz Kacprzyk
Number of pages13
ISBN (Electronic)978-3-319-26986-3
Publication statusPublished - 2016
MoE publication typeA3 Part of a book or another research book

Publication series

NameStudies in Fuzziness and Soft Computing
ISSN (Print)1434-9922


  • Computational intelligence
  • operations research

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    Mezei, J., & Brunelli, M. (2016). Decision analytics and soft computing with industrial partners: A personal retrospective. In M. Collan, M. Fedrizzi, & J. Kacprzyk (Eds.), Fuzzy Technology: Present Applications and Future Challenges (Vol. 335, pp. 193-205). (Studies in Fuzziness and Soft Computing; Vol. 335).