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A Model of Logical Inference and Membership Functions of Factors for the Printing Process Quality Formation

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Lecture Notes in Computational Intelligence and Decision Making (ISDMCI 2019)

Abstract

Technological stages or separate procedures of the publishing and printing process involve relevant databases and a set of factors (criteria, parameters, requirements) to ensure their quality implementation. However, they are different in nature, purpose, setting type, peculiarities of impact and application methods, that complicates the generalizations and single formal reproduction of information. This fact causes the necessity for both bringing them to an universal metric database and using of the methods that would provide the research of the publishing and printing process from the standpoint of a single methodological basis, determining components of which are the methods of system and matrix analysis, the theory of hierarchical multilevel systems, the modelling theory, the operations research and the fuzzy set theory.

The paper presents the model of logic inference, which determines the predictive quality indicators of the process of flatbed offset printing technique on the basis of fuzzy sets. An universal term-set of values and its corresponding linguistic terms of linguistic variables has been formed. The membership functions of linguistic variables have been designed and calculated which are the basis for the structure of the knowledge matrices and fuzzy logic equations as a prerequisite condition of formation and definition of the integral quality indicator of the printing process.

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Correspondence to Sergii Babichev .

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Senkivskyy, V., Pikh, I., Havenko, S., Babichev, S. (2020). A Model of Logical Inference and Membership Functions of Factors for the Printing Process Quality Formation. In: Lytvynenko, V., Babichev, S., Wójcik, W., Vynokurova, O., Vyshemyrskaya, S., Radetskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2019. Advances in Intelligent Systems and Computing, vol 1020. Springer, Cham. https://doi.org/10.1007/978-3-030-26474-1_42

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