An OWA operator with fuzzy ranks

Mitchell, H. B.; Estrakh, D. D.

doi:10.1002/(sici)1098-111x(199801)13:1<69::aid-int6>3.0.co;2-v

Cited by 36 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the essential concepts which we are using is fuzzy OWA operator [12][13][14]. In our multi-criteria decision making approach we are using quite new Fuzzy Heavy Ordered Weighted Averaging (FHOWA) operator introduced in [4] and defined as follows.…”

Section: B Fuzzy Heavy Owamentioning

confidence: 99%

Fuzzy Scorecards, FHOWA, and a New Fuzzy Similarity Based Ranking Method for Selection of Human Resources

Luukka

Collan

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

View full text Add to dashboard Cite

A novel procedure for human resources selection is proposed. Fuzzy scorecards are used to collect information from multiple experts representing different knowledge domains. The results are aggregated by using Fuzzy Heavy Ordered Weighted Averaging (FHOWA) total type aggregation. The results are ranked with a new method, based on using fuzzy similarity to an ideal solution. A numerical example is used for illustration. The procedure preserves more information from evaluation to ranking than previous models.

show abstract

Section: B Fuzzy Heavy Owamentioning

confidence: 99%

Fuzzy Scorecards, FHOWA, and a New Fuzzy Similarity Based Ranking Method for Selection of Human Resources

Luukka

Collan

2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

View full text Add to dashboard Cite

show abstract

“…One of the essential concepts that are used is the Fuzzy Ordered Weighted Averaging (FOWA) operator [7][8][9]. The FOWA operator is an aggregation operator that is here proposed to be used in the aggregation of the multiple linguistic fuzzy assessments.…”

Section: Mathematical Backgroundmentioning

confidence: 99%

Using a Linguistic Scorecard for Peer-Assessment Through an On-Line System

Luukka¹,

Collan²

2013

Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology

View full text Add to dashboard Cite

Peer-assessment is a way to include evaluation as a part of the learning process and simultaneously to cut teacher load in grading of assignments. eLearning systems can be used to automate peer-assessment to a large extent. Peer-assessment benefits from multiplepeer-assessment as it is likely to even-out outliers. Linguistic scorecards can be used to simplify assessment. The linguistic scales can be mapped to fuzzy scales and the results weighted and aggregated to derive an overall assessment. Sometimes ranking of the outcomes is needed. This paper presents the foundations of a system that uses linguistic scorecards in peer-assessment that uses self-evaluation in weighting results, and that ranks the assessments. A numerical example is used to illustrate the system.

show abstract

“…Recently, many attempts have been made in this direction, which include Ahn (2006);and Chang et al (2006); Chen andChen (2005, 2003a); Xu and Da (2002); Carlsson and Fullér (2000);Mitchell and Estrakh (1998). To help understand the concept of FN-OWA, first fuzzy arithmetic and later OWA operators are discussed.…”

Section: Fuzzy Number Owa (Fn-owa)mentioning

confidence: 99%

Developing environmental indices using fuzzy numbers ordered weighted averaging (FN-OWA) operators

Sadiq

Tesfamariam

2007

Stoch Environ Res Risk Assess

View full text Add to dashboard Cite

/npsi/ctrl?lang=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?lang=fr Access and use of this website and the material on it are subject to the Terms and Conditions set forth at http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/jsp/nparc_cp.jsp?lang=en NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.http://dx.doi.org/10.1007/s00477-007-0151-0 Stochastic Environmental Research & Risk Assessment, 22, 1, pp. 495-505, 2008-01-01 Developing environmental indices using fuzzy numbers ordered weighted averaging (FN-OWA) operators Sadiq, R.; Tesfamariam, S. Abstract: Environmental indices (EI) are common communication tool used to describe the overall status of environmental systems (e.g. air, water, soil). Development of EI entails the use of mathematical operators to aggregate various non-commensurate input parameters in a logical manner. Ordered weighted averaging (OWA) operator is a general mean type operator that provides flexibility in the aggregation process such that the aggregated value is bounded between minimum and maximum values of the input parameters. This flexibility of OWA operator is realized through the concept of orness, which is a surrogate for decision maker's attitude.For the development of environmental indices, the type of input parameters also affects the choice of aggregation operators. If the input parameters are linguistic or fuzzy, the aggregation through OWA operators is not possible, and the use of fuzzy arithmetic is warranted. To develop EI, the concept of FN-OWA (fuzzy number OWA) operators is explored to handle the situations when one ore more input parameter has fuzzy (or linguistic) values. The proposed approach is demonstrated using data provided in an earlier study by Swamee and Tyagi (2000) for establishing water quality indices. Multiple hypothetical scenarios are also generated to highlight the utility and the sensitivity of the proposed approach.

show abstract

An OWA operator with fuzzy ranks

Cited by 36 publications

References 0 publications

Fuzzy Scorecards, FHOWA, and a New Fuzzy Similarity Based Ranking Method for Selection of Human Resources

Fuzzy Scorecards, FHOWA, and a New Fuzzy Similarity Based Ranking Method for Selection of Human Resources

Using a Linguistic Scorecard for Peer-Assessment Through an On-Line System

Developing environmental indices using fuzzy numbers ordered weighted averaging (FN-OWA) operators

Contact Info

Product

Resources

About