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Modelling of Knowledge via Fuzzy Knowledge Unit in a Case of the ERP Systems Upgrade

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Abstract

This article is addressed to knowledge modelling and formalization using a fuzzified knowledge unit. The work is based on the system approach to the definition of knowledge units, on the procedural form of knowledge. Fuzzification of knowledge units draws innovation potential from knowledge units with fuzzy linguistic variables and Mamdani fuzzy inference system. Fuzzy knowledge units arise as a join the best properties of the given approaches. The core is the knowledge unit itself comprising the description of a problem and its solution. The typical knowledge unit consists of four elements – X as problem situation, Y as elementary problem, Z as goal of elementary problem solving and Q as solution of elementary problem. A last element of a knowledge unit Q is fuzzified by fuzzy linguistic variable. Steps of fuzzification process are described in the case study “Process customization.” The discussion unifies the findings from the chapters with results of the case study.

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Funding

This work was supported by Internal Grant Agency of the FEM CULS Prague “Data, information and knowledge in expert systems,” grant no. 20171026.

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Authors and Affiliations

  1. Department of Systems Engineering, Czech University of Life Sciences, 16521, Prague, Czech Republic

    Michal Peták, Helena Brožová & Milan Houška

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  1. Michal Peták
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  2. Helena Brožová
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  3. Milan Houška
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Corresponding authors

Correspondence to Michal Peták, Helena Brožová or Milan Houška.

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Michal Peták, Brožová, H. & Houška, M. Modelling of Knowledge via Fuzzy Knowledge Unit in a Case of the ERP Systems Upgrade. Aut. Control Comp. Sci. 54, 529–540 (2020). https://doi.org/10.3103/S0146411620060061

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  • DOI: https://doi.org/10.3103/S0146411620060061

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