Discovering Fuzzy Partial Periodic Patterns in Quantitative Irregular Multiple Time Series-Reference-Cited by-同舟云学术

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Discovering Fuzzy Partial Periodic Patterns in Quantitative Irregular Multiple Time Series

Published:2023-08-13 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Fuzzy Systems (FUZZ)
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Author:

Veena Pamalla¹,Likhitha Palla²,Kiran R. Uday²,Luna Jose Maria³,Fournier-Viger Philippe⁴,Zettsu Koji⁵

Affiliation:

1. Sri Balaji PG college, Affiliated to JNTU-Ananthapur,Ananthapur,AP,India

2. The University of Aizu, Japan,Aizu-Wakamatsu,Japan

3. University of Córdoba,Computing and Numerical Analysis,Córdoba,Spain

4. Big Data Institute, Shenzhen University,Shenzhen,China

5. National Institute of Information and Communications Technology,Tokyo,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10309665/10309668/10309773.pdf?arnumber=10309773

Reference22 articles.

1. Fuzzy-driven periodic frequent pattern mining

2. Fast algorithms for mining multiple fuzzy frequent itemsets

3. Discovering Fuzzy Geo-referenced Periodic-Frequent Patterns in Geo-referenced Time Series Databases

4. Discovering Fuzzy Periodic-Frequent Patterns in Quantitative Temporal Databases

5. New and efficient knowledge discovery of partial periodic patterns with multiple minimum supports

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