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International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 4 Issue 4, 2015.
Abstract: Data granulation is considered a good tool of decision making in various types of real life applications. The basic ideas of data granulation have appeared in many fields, such as interval analysis, quantization, rough set theory, Dempster-Shafer theory of belief functions, divide and conquer, cluster analysis, machine learning, databases, information retrieval, and many others. Some new topological tools for data granulation using rough set approximations are initiated. Moreover, some topological measures of data granulation in topological information systems are defined. Topological generalizations using dß -open sets and their applications of information granulation are developed.
A. S. Salama, “Accurate Topological Measures for Rough Sets” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 4(4), 2015. http://dx.doi.org/10.14569/IJARAI.2015.040405
@article{Salama2015,
title = {Accurate Topological Measures for Rough Sets},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2015.040405},
url = {http://dx.doi.org/10.14569/IJARAI.2015.040405},
year = {2015},
publisher = {The Science and Information Organization},
volume = {4},
number = {4},
author = {A. S. Salama}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.