Title :
Information granulation: percepts and their stability
Author :
Pedrycz, Witold ; Smith, Michael H.
Author_Institution :
Dept. of Electr. & Comput. Eng., Alberta Univ., Edmonton, Alta., Canada
Abstract :
Introduces a notion of relevance (conceptual stability) of information granules. Granulation of data results in a series of chunks of information usually referred to as information granules. These information granules are basic building entities involved in the design of a broad class of systems. Information granules are also percepts-entities being perceived by humans as being essential while working with some real-world phenomena, especially describing and interacting with them. The percepts need to be comprehensible. They should also reflect the experimental evidence. Furthermore, information granules should be stable, meaning that they reconcile experimental reality with the subjective and ultimately observer-based judgement about the environment. Once being stable, information granules could be viewed as independent. The proposed environment supporting this concept dwells on the ideas of statistical inference that helps quantify stability thorough nonparametric testing
Keywords :
fuzzy set theory; nonparametric statistics; conceptual stability; experimental reality; information granulation; information granules; nonparametric testing; observer-based judgement; real-world phenomena; relevance; statistical inference; Buildings; Computer aided manufacturing; Fuzzy sets; Humans; Inference algorithms; Information processing; Pulp manufacturing; Stability; Testing; Vehicles;
Conference_Titel :
Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-5877-5
DOI :
10.1109/FUZZY.2000.838638