title: |
Reducing Positive Leniency in Fuzzy Measure Ratings |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-01-7 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/jcis.2006.18 (how to use a DOI) | |
author(s): |
Ting-Yu Chen, Jih-Chang Wang |
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corresponding author: |
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publication date: |
October 2006 |
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keywords: |
Fuzzy Measure, Positive Leniency, Fuzzy Distance Measure |
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abstract: |
Fuzzy measures have been widely used to determine the degrees of subjective importance of evaluation items. However, the leniency error may exist when most attributes are assigned unduly high ratings. Because respondents often assign similarly complimentary scores, errors of positive leniency make it difficult to differentiate the importance of decision attributes. To reduce positive leniency in fuzzy measure ratings, we develop a method by comparison of fuzzy number-valued fuzzy measures using a fuzzy distance measure. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |