Data-Based Technique for Extracting Knowledge from Data Generated in Experiments

ZAPOROJAN, Sergiu; CARBUNE, Viorel; CALMICOV, Igori

dc.contributor.author	ZAPOROJAN, Sergiu
dc.contributor.author	CARBUNE, Viorel
dc.contributor.author	CALMICOV, Igori
dc.date.accessioned	2021-10-12T09:02:28Z
dc.date.available	2021-10-12T09:02:28Z
dc.date.issued	2020
dc.identifier.citation	ZAPOROJAN, Sergiu, CARBUNE Viorel, CALMICOV, Igori. Data-Based Technique for Extracting Knowledge from Data Generated in Experiments. In: 16th International Conference on Intelligent Computer Communication and Processing: proc. 16th IEEE ICCP, 3-5 Sept. 2020, Cluj-Napoca, Romania, 2020, pp13-19. ISBN 978-1-7281-9080-8.	en_US
dc.identifier.isbn	978-1-7281-9080-8
dc.identifier.uri	https://doi.org/10.1109/ICCP51029.2020.9266187
dc.identifier.uri	http://repository.utm.md/handle/5014/17687
dc.description	Access full text - https://doi.org/10.1109/ICCP51029.2020.9266187	en_US
dc.description.abstract	Fuzzy sets are used in different fields and determination of the membership functions is one of the most important issues in the design of fuzzy systems. The paper presents an approach to that problem to provide solutions in specific cases. In context, a technique for extracting knowledge from measurements data sets was developed that allows to retrieve human expertise and the construction of algorithms for decision-making systems. Initially, the method was developed to be used in data-based fuzzy modeling for the micro-wire casting plant control.	en_US
dc.language.iso	en	en_US
dc.publisher	IEEE	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	experiments data	en_US
dc.subject	fuzzy systems	en_US
dc.subject	measurements data	en_US
dc.subject	decision-making systems	en_US
dc.title	Data-Based Technique for Extracting Knowledge from Data Generated in Experiments	en_US
dc.type	Article	en_US