@inproceedings{81644d07e0ac4883bb3fdca19b3e40cd,
title = "Fuzzy Sets and Rough Sets for Scenario Modelling and Analysis",
abstract = "Both fuzzy set theory and rough set theory play an important role in data-driven, systems modelling and analysis. They have been successfully applied to building various intelligent decision support systems (amongst many others). This paper presents an integrated utilisation of some recent advances in these theories for detection and prevention of serious crime (e.g. terrorism). It is shown that the use of these advanced theories offers an effective means for the generation and assessment of plausible scenarios which can each provide an explanation for the given intelligence data. The resulting systems have the potential to facilitate rapid response in devising and deploying preventive measures. The paper also suggests a number of important further challenges in consolidating and refining such systems.",
author = "Qiang Shen",
note = "Q. Shen. Fuzzy sets and rough sets for scenario modelling and analysis. Proceedings of the 12th International Conference on Rough Sets, LNAI 5908, pp. 45-58, 2009. Sponsorship: EPSRC; 12th International Conference, RSFDGrC 2009 ; Conference date: 15-12-2009 Through 18-12-2009",
year = "2009",
doi = "10.1007/978-3-642-10646-0_5",
language = "English",
isbn = "978-3-642-10645-3",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "45--58",
editor = "Hiroshi Sakai and Chakroborty, {Mihir Kumar} and Hassanien, {Aboul Ella} and Dominik {\'S}l{\c e}zak and William Zhu",
booktitle = "Rough Sets, Fuzzy Sets, Data Mining and Granular Computing",
address = "Switzerland",
}
