A Method for Dealing with Multi-granularity and Multi-scale Linguistic Information based on Modified Proportional 2-tuples
-
- 발행기관
- 보안공학연구지원센터(IJDTA) 바로가기
-
- 간행물
- International Journal of Database Theory and Application SCOPUS 바로가기
-
- 통권
- Vol.9 No.2 (2016.02)바로가기
-
- 페이지
- pp.251-266
-
- 저자
-
- 언어
- 영어(ENG)
-
- URL
- https://www.earticle.net/Article/A271275
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Multi-granularity linguistic information has been studied by researchers in many disciplines, in which the scale of linguistic term sets is usually restricted in domain [0, 1]. In this paper, we consider the multiple attribute group decision making (MAGDM) problems, in which the evaluation of each alternative with respect to each attribute is provided by several experts of the corresponding field. In order to convey the preferences of different experts exactly and to describe the characteristics of different attributes, linguistic term sets with different granularities and different scales have been proposed to express their evaluation values. Moreover, the performance values given by the experts take the form of modified proportional 2-tuples. In this process, the modified proportional 2-tuple, its comparative rules as well as several aggregation operators have been proposed. A new method has been proposed to achieve a basic modified linguistic term set (BMLTS) and a transformation function has been defined to make the performance values uniform. An example is given to illustrate the applicability and flexibility of the method.
목차
Abstract
1. Introduction
2. Preliminaries
2.1. Notions of 2-tuple Linguistic Representation Model
2.2. Proportional 2-tuple Linguistic Representation Model
3. Modified Proportional 2-tuple Fuzzy Linguistic Representation Model
3.1. Notions for Modified Proportional 2-tuple
3.2. The Comparative Rules and Aggregation Operators of Modified Proportional 2-tuples
4. Fusion Approach for Managing Multi-granularity and Multi-scale Linguistic Information based on Modified Proportional 2-tuple
4.1. Setting up basic Modified Linguistic Term Set (BMLTS)
4.2. Getting Linguistic Terms of BMLTS
4.3. Transforming Performance Values into Linguistic Information of BMLTS
5 . Illustrative Examples
6. Conclusions
Acknowledgements
References
키워드
Multiple attribute group decision making Computing with words Linguistic variables Linguistic modeling Multi-granularity linguistic term sets Multiple scale linguistic term sets저자
간행물 정보
발행기관
-
- 발행기관명
- 보안공학연구지원센터(IJDTA) [Science & Engineering Research Support Center, Republic of Korea(IJDTA)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
-
- 간행물명
- International Journal of Database Theory and Application
- 간기
- 격월간
- pISSN
- 2005-4270
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Database Theory and Application Vol.9 No.2
피인용수 : 0건 (자료제공 : 네이버학술정보)
함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.
0개의 논문이 장바구니에 담겼습니다.