Further remarks on the relation between rough and fuzzy sets
Fuzzy Sets and Systems
Similarity, interpolation, and fuzzy rule construction
Fuzzy Sets and Systems - Special issue on expert decision support systems
A comparative study of fuzzy sets and rough sets
Information Sciences: an International Journal
Attribute reduction based on evidence theory in incomplete decision systems
Information Sciences: an International Journal
Rough set theory for the interval-valued fuzzy information systems
Information Sciences: an International Journal
Computers & Mathematics with Applications
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Information Technology and Management
Expert Systems with Applications: An International Journal
Fuzzy rough DEA model: A possibility and expected value approaches
Expert Systems with Applications: An International Journal
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In this paper, we present the concept of fuzzy information granule based on a relatively weaker fuzzy similarity relation called fuzzy T"L-similarity relation for the first time. Then, according to the fuzzy information granule, we define the lower and upper approximations of fuzzy sets and a corresponding new fuzzy rough set. Furthermore, we construct a kind of new fuzzy information system based on the fuzzy T"L-similarity relation and study its reduction using the fuzzy rough set. At last, we apply the reduction method based on the defined fuzzy rough set in the above fuzzy information system to the reduction of the redundant multiple fuzzy rule in the scheduling problems, and numerical computational results show that the reduction method based on the new fuzzy rough set is more suitable for the reduction of multiple fuzzy rules in the scheduling problems compared with the reduction methods based on the existing fuzzy rough set.