Paper Info
Title
TrPM: A Linguistic Petri Nets module to describe the trends of a time series
Abstract
Linguistic Petri Net (LPN) is a method to generate linguistic descriptions, which maintains the way that Petri Nets (PNs) work along with the mechanisms necessary to generate linguistic descriptions of systems. This paper presents a new LPN module, called the Trends Processing Module (TrPM), to generate linguistic descriptions of trends in a time series. This takes the series as an input and returns a sequence of places that represent in detail each one of the trends of the series, which allows us to generate the description. A public dataset has been used to test the presented module. The designed module can be used to design another more complex LPNs that need an approximate model of the trends of a time series.
Year
DOI
Venue
2020
10.1109/FUZZ48607.2020.9177729
2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Keywords
DocType
ISSN
Natural language description,linguistics Petri Nets,fuzzy logic,time series analysis
Conference
1544-5615
ISBN
Citations 
PageRank 
978-1-7281-6933-0
0
0.34
References 
Authors
13
3
Name
Order
Citations
PageRank
Juan Moreno García13711.25
Ester Del Castillo251.14
L. Rodriguez-Benitez3698.81