Rough set theory is a new soft computing tool which deals with vagueness and uncertainty. It has attracted the attention of researchers and practitioners worldwide, and has been successfully applied to many fields such as knowledge discovery, decision support, pattern recognition, and machine learning. Rough Computing: Theories, Technologies and Applications offers the most comprehensive coverage of key rough computing research, surveying a full range of topics from granular computing to pansystems theory. With its unique coverage of the defining issues of the field, this commanding research collection provides libraries with a single, authoritative reference to this highly advanced technological topic.
Aboul Ella Hassanien received a BSc (Hons) and an MSc, both from Ain Shams University, Faculty of Science, Pure Mathematics and Computer Science Department, Cairo, Egypt. In 1998, he received his doctoral degree from the Department of Computer Science, Graduate School of Science & Engineering, Tokyo Institute of Technology, Japan. Currently, he is an associate professor at Cairo University, Faculty of Computer and Information, IT Department. His research interests include rough set theory, wavelet theory, x-ray mammogram analysis, medical image analysis, fuzzy image processing and multimedia data mining.
Zbigniew Suraj received an MSc from the Pedagogical University in Rzeszów (Poland), a PhD from the Warsaw University in mathematics, and a DSc (habilitation) in computer science from the Institute of Computer Science, Polish Academy of Sciences. He is presently a professor at the University of Rzeszów (Poland), head of the Chair of Computer Science at the University. His recent research interests focus on concurrency, rough set theory and its applications, knowledge discovery, data mining, and approximate reasoning.
Dominik l zak received a PhD in computer science from Warsaw University, Poland. He serves as an executive member of the International Rough Set Society, editor-in-chief of Online International Journal on Rough Set Methods, guest editor and reviewer for a number of international scientific journals, chair of several international scientific conferences, and is a member of several IEEE technical committees.
Pawan Lingras is a professor and chairperson of the Department of Mathematics and Computing Science at Saint Mary s University, Halifax, Canada. His undergraduate education from Indian Institute of Technology, Bombay, India was followed by graduate studies at the University of Regina, Canada. His areas of interests include artificial intelligence, information retrieval, data mining, Web intelligence, and intelligent transportation systems.
