ON MODELING UNCERTAINTY WITH INTERVAL STRUCTURES
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 406-426 |
| Journal / Publication | Computational Intelligence |
| Volume | 11 |
| Issue number | 2 |
| Publication status | Published - May 1995 |
| Externally published | Yes |
Link(s)
Abstract
In this paper, we introduce the notion of interval structures in an attempt to establish a unified framework for representing uncertain information. Two views are suggested for the interpretation of an interval structure. A typical example using the compatibility view is the rough set model in which the lower and upper approximations form an interval structure. Incidence calculus adopts the allocation view in which an interval structure is defined by the tightest lower and upper incidence bounds. The relationship between interval structures and interval‐based numeric belief and plausibility functions is also examined. As an application of the proposed model, an algorithm is developed for computing the tightest incidence bounds. Copyright © 1995, Wiley Blackwell. All rights reserved
Research Area(s)
- belief functions, incidence calculus, interval structure, knowledge representation, rough sets, uncertainty management
Bibliographic Note
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Citation Format(s)
ON MODELING UNCERTAINTY WITH INTERVAL STRUCTURES. / Wong, S. K.M.; Wang, L. S.; Yao, Y. Y.
In: Computational Intelligence, Vol. 11, No. 2, 05.1995, p. 406-426.
In: Computational Intelligence, Vol. 11, No. 2, 05.1995, p. 406-426.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
