id: 25386
Title: Determination of similarity criteria in optimization tasks by means of neuro-fuzzy modelling = Визначення критеріїв подібності в задачах оптимізації за допомогою нейро-нечіткого моделювання
Authors: Rubanenko O. O., Komar V. O., Petrushenko O. Y., Smolarz A., Smailova S., Imanbekova U.
Keywords: similarity theory, neuro-fuzzy modelling, basic similarity criteria, membership functions, uncertainty
Date of publication: 2020-07-21 12:31:35
Last changes: 2020-07-21 12:31:35
Year of publication: 2017
Summary: A method is proposed for solving optimization problems with high complexity when searching for the function minimum by using methods and means of similarity theory and neuro-fuzzy modelling. The problem with nonlinear objective function and constraints is transformed into a task with a nonlinear objective function and linear constraints. In this task, the basic similarity criteria are presented in the form of membership functions.
Dependent similarity criteria are defined through the base with the use of standard computational procedures.
URI: http://repository.vsau.org/repository/getfile.php/25386.pdf
Publication type: Статті Scopus
Publication: Przegląd elektrotechniczny. 2017. - R. 93, NR 3. - P. 93-96.
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Published by: Адміністратор
File : 25386.pdf Size : 396596 byte Format : Adobe PDF Access : Only for VNAU users
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