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Forefront of Fuzzy Logic in Data Mining: Theory, Algorithms, and Applications

Call for Papers

Data mining uses various techniques and theories from a wide range of areas for the knowledge extraction from large volumes of data. However, uncertainty is a widespread phenomenon in data mining problems. Accordingly, fuzzy logic is applied to cope with the uncertainty in real world.

The aim of this special issue has twofold: (i) to present recent outstanding developments and trends in the theory and algorithms of data mining using fuzzy logic and (ii) to create a multidisciplinary forum of discussion on recent advances in data mining as well as new applications to biology, economics, ecology, engineering, finance, management, medicine, and so on using fuzzy logic.

Since data mining technology is widely studied and applied in various areas of science, we invite all the related researchers from the fields of computer science, engineering, statistics, economy, finance, marketing, social sciences, healthcare, and so on.

Potential topics include, but are not limited to:

  • Clustering
  • Classification
  • Support vector machines
  • Neural networks
  • Sequential data analysis
  • Pattern recognition
  • Machine learning
  • Fuzzy statistics
  • Real-world applications of data mining in finance, economics, engineering, biology, medicine, image processing, and so on

Authors can submit their manuscripts via the Manuscript Tracking System at http://mts.hindawi.com/submit/journals/afs/ffld/.

Manuscript DueFriday, 29 July 2016
First Round of ReviewsFriday, 21 October 2016
Publication DateFriday, 16 December 2016

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Guest Editors