Work place: SITE, VIT University, Vellore, Tamil Nadu, India
T. K. Das, received his M. Tech. in computer science from Utkal university, India in the year 2003 and M. Sc. from Berhampur University, India in the year 1995. He is currently working as Assistant Professor-Senior and is pursuing his Ph. D. at VIT University, India. He has authored many international journal and conference papers to his credit. His research interests include Artificial Intelligence, Data Analysis and Data Mining, Databases. He is associated with many professional bodies CSI, and ISCA.
DOI: https://doi.org/10.5815/ijisa.2015.04.04, Pub. Date: 8 Mar. 2015
Convergence of information and communication technology has brought a radical change in the way data are collected or generated for ease of multi criterion decision making. The huge data is of no use unless it provides certain information. It is very tedious to select a best option among an array of alternatives. Also, it becomes more tedious when the data contains uncertainties and objectives of evaluation vary in importance and scope. Unlocking the hidden data is of no use to gain insight into customers, markets and organizations. Therefore, processing these data for obtaining decisions is of great challenge. Based on decision theory, in the past many methods are introduced to solve multi criterion decision making problem. The limitation of these approaches is that, they consider only certain information of the weights and decision values to make decisions. Alternatively, it makes less useful when managing uncertain and vague information. In addition, an information system establishes relation between two universal sets. In such situations, multi criterion decision making is very challenging. Therefore, an effort has been made in this paper to process inconsistencies in data with the introduction of intuitionistic fuzzy rough set theory on two universal sets.[...] Read more.
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