Measure of roughness using granular computing
R. B. Patel, Sonajharia Minz
Abstract
R. B. Patel, Sonajharia Minz
Abstract
The problem of handling imprecision, vagueness and uncertainty in data has been attempted for a long time by philosophers, logicians and mathematicians. Recently there have been many approaches explored to understand and manipulate the imprecise knowledge. The most successful one is fuzzy set theory proposed by Zadeh. The theory of Rough set is a relatively new mathematical approach to decision making in data characterized by imprecision, vagueness and uncertainty. This paper examines, Measure of roughness of information granules may be one tool to manipulate the useful knowledge hidden in uncertain and imprecise data. The measure of roughness of information granules may possibly give knowledge about information system with precision.
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The problem of handling imprecision, vagueness and uncertainty in data has been attempted for a long time by philosophers, logicians and mathematicians. Recently there have been many approaches explored to understand and manipulate the imprecise knowledge. The most successful one is fuzzy set theory proposed by Zadeh. The theory of Rough set is a relatively new mathematical approach to decision making in data characterized by imprecision, vagueness and uncertainty. This paper examines, Measure of roughness of information granules may be one tool to manipulate the useful knowledge hidden in uncertain and imprecise data. The measure of roughness of information granules may possibly give knowledge about information system with precision.
Key concepts: Vagueness, Rough set, Granular computing, Measure (data warehouse), Fuzzy set, Computer science, Set (abstract data type), Fuzzy logic