DocumentCode :
1177227
Title :
Multiresolutional hierarchical decision support systems
Author :
Meystel, A.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
Volume :
33
Issue :
1
fYear :
2003
Firstpage :
86
Lastpage :
101
Abstract :
Decision support systems gain better performance and higher accuracy by the virtue of building multiresolutional (multigranular, multiscale) representation, and employing multiscale behavior generation subsystem (planning and control). The latter are equipped by devices for unsupervised learning that adjust their functioning to the results of self-identification. We demonstrate that planning and learning are joint processes. The author´s intention is to emphasize that the concepts of multiresolutional representation (MR) and multiresolutional decision support (MR-DSS) probably have in common a general significance that crosses the boundaries of particular domains of applications and disciplines. The paper explores this phenomenon. The ubiquity of a principle that somehow persistently delivers benefits to many areas of knowledge and technology seems to be more important than a habit to follow the pigeonhole principle of paper presentation.
Keywords :
decision making; decision support systems; generalisation (artificial intelligence); knowledge management; decision support systems; dynamic programming; generalization; indistinguishability; instantiation; knowledge; knowledge management; multigranular; multiresolutional; multiresolutional decision support; multiresolutional representation; multiscale; Control systems; Decision support systems; Dynamic programming; Image edge detection; Image resolution; Paper technology; Performance gain; Process planning; Signal resolution; Unsupervised learning;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher :
ieee
ISSN :
1094-6977
Type :
jour
DOI :
10.1109/TSMCC.2003.809866
Filename :
1193064
Link To Document :
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