M. Nagaraju

Work place: SCSE, VIT University, Vellore-632 014, Tamil Nadu, INDIA

E-mail: mnagaraju@vit.ac.in

Website:

Research Interests: Computer systems and computational processes, Data Mining, Database Management System, Decision Support System

Biography

M. Nagaraju is a assistant professor (senior) in the school of computing sciences and engineering, VIT University, Vellore, India. He is pursuing his Ph.D. Degree in computer science in the same school. He is a life member in professional associations like ISTE and CSI. His current research interest includes Fuzzy sets and systems, Rough sets and knowledge engineering, Granular computing, Database systems, Expert Systems, Data Mining and Decision Support Systems.

Author Articles
A Comparative Analysis of Multigranular Approaches and on Topoligical Properties of Incomplete Pessimistic Multigranular Rough Fuzzy Sets

By B.K. Tripathy M. Nagaraju

DOI: https://doi.org/10.5815/ijisa.2012.11.12, Pub. Date: 8 Oct. 2012

Rough sets, introduced by Pawlak as a model to capture impreciseness in data have been a very useful tool in several applications. These basic rough sets are defined by taking equivalence relations over a universe. In order to enhance the modeling powers of rough sets, several extensions to the basic definition has been introduced over the past few years. Extending the single granular structure of research in classical rough set theory two notions of Multigranular approaches; Optimistic Multigranulation and Pessimistic Multigranulation have been introduced so far. Topological properties of rough sets along with accuracy measures are two important features of rough sets from the application point of view. Topological properties of Optimistic Multigranular rough sets Optimistic Multigranular rough fuzzy sets and Pessimistic Multigranular rough sets have been studied. Incomplete information systems take care of missing values for items in data tables. Optimistic and pessimistic MGRS have also been extended to such type of incomplete information systems. In this paper we provide a comparative study of the two types of Multigranular approaches along with other related notions. Also, we extend the study to topological properties of incomplete pessimistic MGRFS. These results hold both for complete and incomplete information systems.

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On Some Topological Properties of Pessimistic Multigranular Rough Sets

By B.K. Tripathy M. Nagaraju

DOI: https://doi.org/10.5815/ijisa.2012.08.02, Pub. Date: 8 Jul. 2012

Rough set theory was introduced by Pawlak as a model to capture impreciseness in data and since then it has been established to be a very efficient tool for this purpose. The definition of basic rough sets depends upon a single equivalence relation defined on the universe or several equivalence relations taken one each at a time. There have been several extensions to the basic rough sets introduced since then in the literature. From the granular computing point of view, research in classical rough set theory is done by taking a single granulation. It has been extended to multigranular rough set (MGRS) model, where the set approximations are defined by taking multiple equivalence relations on the universe simultaneously. Multigranular rough sets are of two types; namely optimistic MGRS and pessimistic MGRS. Topological properties of rough sets introduced by Pawlak in terms of their types were studied by Tripathy and Mitra to find the types of the union, intersection and complement of such sets. Tripathy and Raghavan have extended the topological properties of basic single granular rough sets to the optimistic MGRS context. Incomplete information systems take care of missing values for items in data tables. MGRS has also been extended to such type of incomplete information systems. In this paper we have carried out the study of topological properties of pessimistic MGRS by finding out the types of the union, intersection and complement of such sets. Also, we have provided proofs and examples to illustrate that the multiple entries in the table can actually occur in practice. Our results hold for both complete and incomplete information systems. The multiple entries in the tables occur due to impreciseness and ambiguity in the information. This is very common in many of the real life situations and needed to be addressed to handle such situations in efficient manner.

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