Визначення точності нечіткої моделі технологічного форсайта / Купчин А. В., Комаров В. С., Борохвостов І. В., Білокур М. О., Купріненко О. М., Міщенко Я. С., Богданович В. Ю., Кононов О. А. (2022)
Ukrainian

English  Cybernetics and Systems Analysis   /     Issue (2022, 58 (3))

Kupchyn A., Komarov V., Borokhvostov I., Bilokur M., Kuprinenko A., Mishchenko Y., Bohdanovych V., Kononov O.
Determining the accuracy of a fuzzy model of the technology foresight

A method for checking the accuracy of prognostic models in the absence of experimental data for comparing the modeling results is presented. The developed neural network determines a technology class, which is compared with the results obtained using the fuzzy logic model. The model accuracy is determined by computing the root-mean-square error of the modeling and the correlation between the results obtained using the fuzzy logic model and the neural network. © 2022, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: critical technology foresight, fuzzy logic, model accuracy, modeling error, neural network, Engineering education, Fuzzy inference, Fuzzy neural networks, Mean square error, Critical technologies, Critical technology foresight, Fuzzy logic modeling, Fuzzy-Logic, Logic technology, Model errors, Modeling accuracy, Neural-networks, Prognostic modeling, Technology foresight, Computer circuits


Cite:
Kupchyn A., Komarov V., Borokhvostov I., Bilokur M., Kuprinenko A., Mishchenko Y., Bohdanovych V., Kononov O. (2022). Determining the accuracy of a fuzzy model of the technology foresight. Cybernetics and Systems Analysis, 58 (3), 72–82. doi: https://doi.org/10.1007/s10559-022-00470-1 http://jnas.nbuv.gov.ua/article/UJRN-0001323858 [In Ukrainian].


 

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