Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Temporal granulation and its application to signal analysis
Information Sciences—Informatics and Computer Science: An International Journal
Data mining, rough sets and granular computing
Data mining, rough sets and granular computing
Data mining, rough sets and granular computing
Shadowed sets: representing and processing fuzzy sets
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Abstraction and specialization of information granules
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Granular clustering: a granular signature of data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Recursive information granulation: aggregation and interpretation issues
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Relational and directional aspects in the construction of information granules
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Granulation-based symbolic representation of time series and semi-supervised classification
Computers & Mathematics with Applications
Hybrid soft computing systems for reservoir PVT properties prediction
Computers & Geosciences
A genetic design of linguistic terms for fuzzy rule based classifiers
International Journal of Approximate Reasoning
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
Engineering Applications of Artificial Intelligence
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Granulation of information has become an underlying concept permeating a vast array of pursuits. In this study, we address a fundamental issue of the design of ''meaningful'' information granules. The underlying principle guiding their development realizes a tradeoff between a specificity of information granule (which we want to keep as high as possible) and the associated experimental evidence (which needs to be maintained high as well). Recognizing the fact that these are directly in conflict, we formulate the problem as a certain optimization task. In the sequel, we discuss the solutions and analyze their properties. In particular, we will deal with an array of parametric optimization dealing with various commonly encountered types of membership functions.