B k tripathy

Anirban mitra

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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International Journal of Granular Computing, Rough Sets and Intelligent Systems

Several tasks under human activities need to be performed in a sequence of navigation and manipulation of objects. In several applications of human activities like robotics monitoring plays an important role. So, in these applications, processing of sequential data is of utmost importance. Because of the presence of imprecision intelligent clustering approaches using fuzzy or rough set techniques play a major role. The basic rough sets which are defined by using equivalence relations is less useful because of their scarcity in real life scenarios. As a result, covering based rough sets have been introduced which are more general and applicable to real world problems. In this paper, covering rough set based clustering approach is introduced and studied using refined first type of covering based rough sets. Through experimental analysis,illustrated the efficiency of proposed algorithm and provided a comparative analysis of this algorithm with other existing algorithms.

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International Journal of Intelligent Information Technologies

Covering Rough Clustering Approach for Unstructured Activity Analysis

Clustering is categorised as hard or soft in nature. Soft clusters may have fuzzy or rough boundaries. Rough clustering can help researchers to discover overlapping clusters in many applications such as web mining and text mining. Rough set approach is a very useful tool to handle the unclear and ambiguous data. As rough sets make use of the equivalence relation property, they remain rigid and it is unreliable and inefficient for real time applications where the datasets may be very large. In this paper, we provide a solution to this problem with covering-based rough set approach. Covering-based rough set is an extension of rough set approach in which the equivalence relation has been relaxed. This method is based on coverings rather than partitions. This makes it more flexible than rough sets and it is more convenient for dealing with complex applications. Clustering sequential data is one of the vital research tasks. We uses covering-based similarity measure which gives better results as compared to rough set which uses set and sequence similarity measure. In this paper, covering-based rough fuzzy set clustering approach is proposed to resolve the uncertainty of sequence data. © 2015 Inderscience Enterprises Ltd.

International Journal of Reasoning-based Intelligent Systems

An integrated covering-based rough fuzzy set clustering approach for sequential data

2014 IEEE International Conference on Computational Intelligence and Computing Research

Covering based rough clustering of sequential data

Most of the researches in feature selection deal with homogeneous features that are with either numerical or categorical features. As discussed in [2] neighbourhood rough set model is one approach which deals with heterogeneous feature selection. The neighbourhood model is used to reduce numerical and categorical features by assigning different thresholds for different kinds of attributes. Recently Neighbourhood Based Multigranular Rough sets (NMGRS) was introduced and their properties were studied. We shall provide some critical appreciations of the results of this paper. One of the two characteristics used in real life applications of rough sets is their topological characterisations. In this article we study topological characteristics NMGRS. Some interesting algebraic properties of MGRSs were studied recently in [3]. We extend these studies to the NMGRS context. We shall also be illustrating the concepts a real life example. © 2014 IEEE.

2014 International Conference on Computer Communication and Informatics

On algebraic and topological properties of Neighbourhood Based Multigranular Rough Sets

The notion of rough sets [4] was used by Novotny and Pawlak [1, 2, 3] to introduce the concept of rough equality, in order to incorporate user knowledge in determining the equality of sets, which is a natural phenomenon in day to day life. Even this notion was shown to be deficient and was extended by Tripathy et al [6, 9] to define the notion of rough equivalence of sets, which is more suitable in real life situations. Tripathy [7] added two more approximate equalities to this list in order to complete the kinds of approximate equalities. Algebraic properties of sets with mathematical equality have very little meaning when sets are replaced with rough sets. As a consequence, replacing equality by rough equivalence the algebraic properties were studied by Tripathy et al [10]. In our present work, we have made an analysis of the validity of the algebraic properties with respect to the four kinds of approximate equalities and provide a comparative study to establish that rough equivalence is the best and rough equality is the worst among these approximate equalities with respect to the algebraic properties involving rough sets. The topological characterisations of rough sets leading to four types of rough sets and operations on them [8] are being used in the sequel. We support our descriptions with a running real life example of shares. © 2013 IEEE.

Journal	International Journal of Granular Computing, Rough Sets and Intelligent Systems
Publisher	Inderscience Publishers
ISSN	1757-2703
Open Access	0