2006
DOI: 10.1016/j.ins.2006.02.015
|View full text |Cite
|
Sign up to set email alerts
|

Treating fuzziness in subjective evaluation data

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
9
0

Year Published

2007
2007
2016
2016

Publication Types

Select...
5
4

Relationship

0
9

Authors

Journals

citations
Cited by 24 publications
(13 citation statements)
references
References 19 publications
0
9
0
Order By: Relevance
“…The questionnaire consists of listing Kansei attributes, each of which corresponds to a bipolar pair of Kansei words with a 2K þ 1-point odd qualitative scale. For example, the odd qualitative scale of Kansei attributes can be 5-point scale [36], 7-point scale [32], and 9-point scale [10].…”
Section: Identification and Measurement Of Kansei Attributesmentioning
confidence: 99%
See 1 more Smart Citation
“…The questionnaire consists of listing Kansei attributes, each of which corresponds to a bipolar pair of Kansei words with a 2K þ 1-point odd qualitative scale. For example, the odd qualitative scale of Kansei attributes can be 5-point scale [36], 7-point scale [32], and 9-point scale [10].…”
Section: Identification and Measurement Of Kansei Attributesmentioning
confidence: 99%
“…To obtain Kansei data 0020-0255/$ -see front matter Ó 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.ins.2008.06.023 are also used [28,36] in Kansei evaluation. Moreover, Barone et al [2] proposed a weighted regression approach by means of conjoint analysis, in which attribute importance weights are estimated by using respondent choice time in controlled interviews.…”
Section: Introductionmentioning
confidence: 99%
“…Fuzzy set theory was developed based on the premise that key criteria in human thinking are not numbers, but linguistic terms or labels of fuzzy sets. Several fuzzy MCDM methods have been utilized to integrate various linguistic assessments to determine optimal alternatives [3,7,15,20,25,28,37,41].…”
Section: Introductionmentioning
confidence: 99%
“…In the past, the probability statistics (PS) method [11,[22][23][24][25] was usually used for target control. Along with the development of information and industry technology, at present, people are becoming more and more interested in fuzzy control [1,[3][4][5][6][7][8][9][10]12,13,15,[17][18][19]21,26] and rough sets for target control [2,20,27,28]; again, by the combination of fuzzy sets (FS) theory and rough sets (RS) theory, i.e., fuzzy rough sets (FRS) theory [14,16,29], we can obtain a new control algorithm, which here is called the fuzzy rough (FR) control algorithm. However, what differences are there between the new FR algorithm and the PS algorithm on target control?…”
Section: Introductionmentioning
confidence: 99%