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http://cris.utm.md/handle/5014/640| Title: | Data-Based Technique for Extracting Knowledge from Data Generated in Experiments | Authors: | ZAPOROJAN, Sergiu CARBUNE, Viorel CALMICOV, Igor |
Keywords: | knowledge extraction;data-driven modeling;measurements data set;fuzzy system;membership function | Issue Date: | 2020 | Publisher: | IEEE | Source: | S. Zaporojan, V. Carbune and I. Calmicov, "Data-Based Technique for Extracting Knowledge from Data Generated in Experiments," 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, Romania, 2020, pp. 13-19, doi: 10.1109/ICCP51029.2020.9266187. | Conference: | 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP) | 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. |
URI: | http://cris.utm.md/handle/5014/640 | ISBN: | 978-1-7281-9079-2 | DOI: | 10.1109/ICCP51029.2020.9266187 |
| Appears in Collections: | Journal Articles |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Data_Based_Technique_ZAPOROJAN_Sergiu.pdf | 62.6 kB | Adobe PDF | View/Open |
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