%0 Journal Article %1 conf/isgteurope/TuttelbergK18 %A Singh, Seema %A Hooda, D.S. %A Malik, S.C. %B Fuzzy Rough Information Measures and their Applications %D 2021 %J International Journal of Computational Science and Information Technology (IJCSITY) %K learning machine simulation %N 2 %T Fuzzy Rough Information Measures and their Applications %V 10 %X The degree of roughness characterizes the uncertainty contained in a rough set. The rough entropy was defined to measure the roughness of a rough set. Though, it was effective and useful, but not accurate enough. Some authors use information measure in place of entropy for better understanding which measures the amount of uncertainty contained in fuzzy rough set .In this paper three new fuzzy rough information measures are proposed and their validity is verified. The application of these proposed information measures in decision making problems is studied and also compared with other existing information measures.

@article{conf/isgteurope/TuttelbergK18, abstract = { The degree of roughness characterizes the uncertainty contained in a rough set. The rough entropy was defined to measure the roughness of a rough set. Though, it was effective and useful, but not accurate enough. Some authors use information measure in place of entropy for better understanding which measures the amount of uncertainty contained in fuzzy rough set .In this paper three new fuzzy rough information measures are proposed and their validity is verified. The application of these proposed information measures in decision making problems is studied and also compared with other existing information measures.}, added-at = {2024-10-30T13:41:54.000+0100}, author = {Singh, Seema and Hooda, D.S. and Malik, S.C.}, biburl = {https://www.bibsonomy.org/bibtex/2ffe7e2b1d5cf4887075a217668430254/ijcsity}, booktitle = { Fuzzy Rough Information Measures and their Applications}, ee = {https://doi.org/10.1109/ISGTEurope.2018.8571711}, interhash = {436aa4e1c1be838899a8dbd6fc01682d}, intrahash = {ffe7e2b1d5cf4887075a217668430254}, journal = {International Journal of Computational Science and Information Technology (IJCSITY)}, keywords = {learning machine simulation}, number = 2, timestamp = {2024-10-30T13:41:54.000+0100}, title = { Fuzzy Rough Information Measures and their Applications }, volume = 10, year = 2021 }