Selecting Multiple Evaluator’s Perception-Oriented Relevant Physical Features of Consumer Goods by Using Fuzzy Data Sensitivity and OWA Operators
- DOI
- 10.1080/18756891.2016.1149997How to use a DOI?
- Keywords
- feature selection; fuzzy logic; data sensitivity; OWA operators; Multi-criteria decision making; percolation technique
- Abstract
The assessment of goods quality using experts is costly task in addition to their often unavailability. In this paper, we present a new method for ranking physical features of consumer goods according to their relevancy to multiple evaluators’ perception at different levels and selecting the most important ones for quality characterization. The main contribution of the paper is combining of fuzzy method and ordered weighted averaging (OWA) operators to achieve our aim. The proposed selection method, considered as a Multi-Evaluators and Multi-Criteria Decision Making (ME-MCDM) technique, has been developed using fuzzy sensitivity (FS) criterion for ranking and OWA operator to aggregate the aforementioned ranking lists. Finally, by introducing a smart percolation technique we get automatically the most relevant physical features for a given sensory descriptor. The suggested approach is applied to a selection problem of textile physical features.
- Copyright
- © 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - I. Feki AU - X. Zeng AU - A. Ghith AU - L. Koehl AU - F. Msahli AU - F. Sakli PY - 2016 DA - 2016/04/01 TI - Selecting Multiple Evaluator’s Perception-Oriented Relevant Physical Features of Consumer Goods by Using Fuzzy Data Sensitivity and OWA Operators JO - International Journal of Computational Intelligence Systems SP - 213 EP - 226 VL - 9 IS - 2 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2016.1149997 DO - 10.1080/18756891.2016.1149997 ID - Feki2016 ER -