26,630 research outputs found
Fuzzy Interval-Valued Multi Criteria Based Decision Making for Ranking Features in Multi-Modal 3D Face Recognition
Soodamani Ramalingam, 'Fuzzy interval-valued multi criteria based decision making for ranking features in multi-modal 3D face recognition', Fuzzy Sets and Systems, In Press version available online 13 June 2017. This is an Open Access paper, made available under the Creative Commons license CC BY 4.0 https://creativecommons.org/licenses/by/4.0/This paper describes an application of multi-criteria decision making (MCDM) for multi-modal fusion of features in a 3D face recognition system. A decision making process is outlined that is based on the performance of multi-modal features in a face recognition task involving a set of 3D face databases. In particular, the fuzzy interval valued MCDM technique called TOPSIS is applied for ranking and deciding on the best choice of multi-modal features at the decision stage. It provides a formal mechanism of benchmarking their performances against a set of criteria. The technique demonstrates its ability in scaling up the multi-modal features.Peer reviewedProo
Multicriteria optimization to select images as passwords in recognition based graphical authentication systems
Usability and guessability are two conflicting criteria in assessing the
suitability of an image to be used as password in the recognition based graph -ical authentication systems (RGBSs). We present the first work in this area that
uses a new approach, which effectively integrates a series of techniques in order
to rank images taking into account the values obtained for each of the dimen -sions of usability and guessability, from two user studies. Our approach uses
fuzzy numbers to deal with non commensurable criteria and compares two
multicriteria optimization methods namely, TOPSIS and VIKOR. The results
suggest that VIKOR method is the most applicable to make an objective state-ment about which image type is better suited to be used as password. The paper
also discusses some improvements that could be done to improve the ranking
assessment
A Hypervolume Based Approach to Rank Intuitionistic Fuzzy Sets and Its Extension to Multi-criteria Decision Making Under Uncertainty
Ranking intuitionistic fuzzy sets with distance based ranking methods
requires to calculate the distance between intuitionistic fuzzy set and a
reference point which is known to have either maximum (positive ideal solution)
or minimum (negative ideal solution) value. These group of approaches assume
that as the distance of an intuitionistic fuzzy set to the reference point is
decreases, the similarity of intuitionistic fuzzy set with that point
increases. This is a misconception because an intuitionistic fuzzy set which
has the shortest distance to positive ideal solution does not have to be the
furthest from negative ideal solution for all circumstances when the distance
function is nonlinear. This paper gives a mathematical proof of why this
assumption is not valid for any of the non-linear distance functions and
suggests a hypervolume based ranking approach as an alternative to distance
based ranking. In addition, the suggested ranking approach is extended as a new
multicriteria decision making method, HyperVolume based ASsessment (HVAS). HVAS
is applied for multicriteria assessment of Turkey's energy alternatives.
Results are compared with three well known distance based multicriteria
decision making methods (TOPSIS, VIKOR, and CODAS).Comment: 8 pages, 3 figure
Modelling and optimizing multiple attribute decisions by using fuzzy sets
The purpose of this paper is to present a coherent perspective of modeling and optimizing multiple attribute decisions by using fuzzy sets. In management practice we face most of the time the situation in which a problem have several possible solutions and each solution can be analyzed using multiple criteria models. In the same time, in real life decision making process there is a given level of uncertainty which makes difficult a clear cut analytical analysis. The object of this article is to build a model approach for making multiple criteria decision using fuzzy sets of objects. Elaborating multiple attribute decisions involves performing an assessment and selecting from a given and finite set of possible alternative courses of action in the presence of a given and finite, and usually conflicting set of attributes and criteria.decision making, fuzzy sets, modeling, multiple criteria optimization.
Pairwise Comparison and Distance Measure of Hesitant Fuzzy Linguistic Term Sets
A hesitant fuzzy linguistic term set (HFLTS), allowing experts using several possible linguistic terms to assess a qualitative linguistic variable, is very useful to express people’s hesitancy in practical decision-making problems. Up to now, a little research has been done on the comparison and distance measure of HFLTSs. In this paper, we present a comparison method for HFLTSs based on pairwise comparisons of each linguistic term in the two HFLTSs. Then, a distance measure method based on the pairwise comparison matrix of HFLTSs is proposed, and we prove that this distance is equal to the distance of the average values of HFLTSs, which makes the distance measure much more simple. Finally, the pairwise comparison and distance measure methods are utilized to develop two multicriteria decision-making approaches under hesitant fuzzy linguistic environments. The results analysis shows that our methods in this paper are more reasonable
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