Advances in Fuzzy Systems

Fuzzy Methods for Data Analysis


1Università degli Studi di Napoli Federico II, Napoli, Italy

2University of Ostrava, Ostrava, Czech Republic

Fuzzy Methods for Data Analysis


In recent years many papers have been devoted to the search for increasingly sophisticated methods for heterogeneous high dimensional data analysis. To approach these difficult tasks, fuzzy set theory is often integrated with other computational approaches concerning knowledge discovery for large databases, image analysis, spatial analysis, marketing demand forecasting and financial problems.

An efficient data analysis method must be provided with treatment of large data sets (like long time series, genetic data, big data, spatial data, big data extracted from social networks, etc.), integration of heterogeneous data coming from different data sources, treatment of incomplete information, and so on.

The objective of this special issue is to present relevant researches on fuzzy set theory in data analysis. We invite interested researchers to contribute with original articles describing new approaches involving fuzzy sets for dealing with large heterogeneous datasets.

Potential topics include, but are not limited to:

  • Fuzzy methods in data mining
  • Fuzzy knowledge discovery in relational databases
  • Fuzzy methods for big data
  • Fuzzy methods in spatial data analysis
  • Fuzzy methods in predictive models
  • Fuzzy cloud applications
Advances in Fuzzy Systems
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Acceptance rate12%
Submission to final decision90 days
Acceptance to publication29 days
Journal Citation Indicator0.500
Impact Factor1.3

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