## Rough set theory and granular computing.(English)Zbl 1030.68087

Studies in Fuzziness and Soft Computing. 125. Berlin: Springer. xv, 300 p. EUR 82.00/net; sFr 136.00; £63.00; \$ 99.00 (2003).
Publisher’s description: This monograph presents novel approaches and new results in fundamentals and applications related to rough sets and granular computing. It includes the application of rough sets to real world problems, such as data mining, decision support and sensor fusion. The relationship of rough sets to other important methods of data analysis – Bayes theorem, neurocomputing and pattern recognition is thoroughly examined. Another issue is the rough set based data analysis, including the study of decision making in conflict situations. Recent engineering applications of rough set theory are given, including a processor architecture organization for fast implementation of basic rough set operations and results concerning advanced image processing for unmanned aerial vehicles. New emerging areas of study and applications are presented as well as a wide spectrum of on-going research, which makes the book valuable to all interested in the field of rough set theory and granular computing.
The articles of this volume will be reviewed individually.
Indexed articles:
Pawlak, Zdzisław, Bayes’ theorem – the rough set perspective, 1-12 [Zbl 1094.68668]
Skowron, Andrzej, Approximation spaces in rough neurocomputing, 13-22 [Zbl 1094.68630]
Pal, Sankar K., Soft computing pattern recognition: principles, integrations and data mining, 23-34 [Zbl 1108.68568]
Intan, Rolly; Yao, Y. Y.; Mukaidono, Masao, Generalization of rough sets using weak fuzzy similarity relations, 37-57 [Zbl 1094.68658]
Miyamoto, Sadaaki, Two generalizations of multisets, 59-68 [Zbl 1094.68659]
Tanaka, Hideo; Sugihara, Kazutomi; Maeda, Yutaka, Interval probability and its properties, 69-78 [Zbl 1094.68670]
Polkowski, Lech, On fractal dimension in information systems, 79-87 [Zbl 1094.68660]
Murai, Tetsuya; Nakata, Michinori; Sato, Yoshiharu, A remark on granular reasoning and filtration, 89-96 [Zbl 1094.68667]
Skowron, Andrzej; Stepaniuk, Jarosław; Peters, James F., Towards discovery of relevant patterns from parameterized schemes of information granule construction, 97-108 [Zbl 1094.68662]
Ślȩzak, Dominik, Approximate Markov boundaries and Bayesian networks: Rough set approach, 109-121 [Zbl 1094.68669]
Yao, Y. Y., Mining high order decision rules, 125-135 [Zbl 1094.68663]
Murai, Tetsuya; Nakata, Michinori; Sato, Yoshiharu, Association rules from a point of view of conditional logic, 137-145 [Zbl 1034.03039]
Lin, T. Y.; Louie, Eric, Association rules with additional semantics modeled by binary relations, 147-156 [Zbl 1094.68557]
Hirano, Shoji; Tsumoto, Shusaku, A knowledge-oriented clustering method based on indiscernibility degree of objects, 157-166 [Zbl 1094.68556]
Sakai, Hiroshi, Some effective procedures for data dependencies in information systems, 167-176 [Zbl 1094.68690]
Grzymala-Busse, Jerzy W.; Freeman, Rachel L., Improving rules induced from data describing self-injurious behaviors by changing truncation cutoff and strength, 177-185 [Zbl 1094.68623]
Maheswari, V. Uma; Siromoney, Arul; Mehata, K. M., The variable precision rough set inductive logic programming model and future test cases in Web usage mining, 187-196 [Zbl 1094.68534]
Hassan, Yasser; Tazaki, Eiichiro, Rough set and genetic programming, 197-207 [Zbl 1094.68555]
Deja, Rafał, Rough set approach to conflict analysis, 211-221 [Zbl 1094.68640]
Ngoc Thanh Nguyen, Criteria for concensus susceptibility in conflicts resolving, 223-232 [Zbl 1094.68650]
Miyamoto, Sadaaki; Koga, Takatsugu; Nakayama, Yoichi, $$L_1$$-space based models for clustering and regression: Fuzzy clustering and mixture densities, 233-242 [Zbl 1094.68627]
Guo, Peijun; Tanaka, Hideo, Upper and lower possiblity distributions with rough set concepts, 243-250 [Zbl 1094.68657]
Entani, Tomoe; Ichihashi, Hidetomo; Tanaka, Hideo, Efficiency values based on decision maker’s interval pairwise comparisons, 251-260 [Zbl 1094.68641]
Pawlak, Z.; Peters, J. F.; Skowron, A.; Suraj, Z.; Ramanna, S.; Borkowski, M., Rough measures, rough integrals and sensor fusion, 263-272 [Zbl 1053.28010]
Kanasugi, Akinori, A design of architecture for rough set processor, 273-280 [Zbl 1108.68339]
Shinkawa, Yoshiyuki; Matsumoto, Masao J., Identifying adaptable components – a rough sets style approach, 281-290 [Zbl 1094.68544]
Szczuka, Marcin S.; Nguyen, Hung Son, Analysis of image sequences for the unmanned aerial vehicle, 291-300 [Zbl 1095.68703]

### MSC:

 68T37 Reasoning under uncertainty in the context of artificial intelligence

### Keywords:

Rough set theory; Granular computing