Algorithms on Parameterized Rough-Intuitionistic Fuzzy Classification using a Threshold

Authors

  • D. Latha Department of Computer Science and Engineering, AdikaviNannaya University, Andhra Pradesh, India
  • B. Venkataramana Department of Computer Science & Engineering, Holy Mary Institute of Technology, Hyderabad, India

Keywords:

Rough Sets, intuitionistic fuzzy sets, indexing, decision table

Abstract

Hybridization of Rough Sets with intuitionistic fuzzy sets is commonly in use for deriving several real time applications. However, due to limitations, the parameterized rough sets are found to be more effective than conventional RS Models due to its quality and accuracy. In this aspect, we describe three types of algorithms namely lower, upper and parameterized rough indexing algorithms to index the records of decision table with intuitionistic fuzzy decision attributes and the same are implemented using C Programming.

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Published

2023-03-17

How to Cite

D. Latha, & B. Venkataramana. (2023). Algorithms on Parameterized Rough-Intuitionistic Fuzzy Classification using a Threshold . International Journal of Innovative Analyses and Emerging Technology, 1(4), 173–182. Retrieved from https://oajournals.net/index.php/ijiaet/article/view/1939

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Articles