FUZZ-IEEE 2017 – Special Session Rough sets and Fuzzy Rough Hybridization with bio-inspired optimization techniques
SPECIAL SESSION ORGANIZERS:
Ahmad Taher Azar, ahmad_t_azar (at) ieee.org
Valentina E. Balas, balas (at) drbalas.ro
Camelia Pintea, dr.camelia.pintea (at) ieee.org
Rabie A. Ramadan, rabie (at) rabieramadan.org
Mario Pavone, mpavone (at) dmi.unict.it
Nicolaie Popescu-Bodorin, bodorin (at) ieee.org
Rough set theory is a new mathematical approach to imperfect knowledge. Rough sets have been proposed for a very wide variety of applications. In particular, the rough set approach proved to be important for Artificial Intelligence and cognitive sciences, especially in machine learning, knowledge discovery, data mining, expert systems, approximate reasoning and pattern recognition. The objective of this special session is to showcase the real-world applications of hybridization of rough sets and fuzzy rough sets with bio-inspired optimization techniques and other methods of data exploration and approximate computation. The special emphasis will be put on hybrid solutions combining rough sets with other tools, as well as the importance of utilization of domain knowledge in the data mining and data processing solutions.
SCOPE AND TOPICS
The aim of this special session provides an opportunity for international researchers to share and review recent advances in the foundations, integration architectures, and applications of bio-inspired optimization techniques with rough set and fuzzy rough. The special session aims to solicit original, full length original articles on new findings and developments from researchers, academicians and practitioners from industries, in the area of rough set theory, fuzzy rough, granular computing, knowledge discovery and data mining.
The topics of interest include, but are not limited to:
2017 IEEE International Conference on Fuzzy Systems
Paper Submission: FUZZ-IEEE 2017
The accepted papers to this special session will be published in the conference proceedings of FUZZ-IEEE published by the IEEE.