Journal article
Fuzzy set theory and uncertainty in case-based reasoning
ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, Vol.14(3), pp.121-136
01 Sep 2006
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Case-based reasoning (CBR) is a reasoning methodology that relies on previous experiences, making it well suited to various real world application domains. When we use CBR to solve real world problems, its inherent uncertainty tends to propagate and may be detrimental to the system's quality. Consequently, the quality of a CBR system's outcome tends to increase as we address its uncertainty. This article examines approaches based on fuzzy set theory that manage the uncertainty originated in CBR systems and describes in detail a method based to address the uncertainty originated in the CBR assumption that similar problems have similar solutions.
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Details
- Title
- Fuzzy set theory and uncertainty in case-based reasoning
- Creators
- R. Weber
- Publication Details
- ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, Vol.14(3), pp.121-136
- Publisher
- C R L Publishing Ltd
- Number of pages
- 16
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Identifiers
- 991019174898404721
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- Web of Science research areas
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic