105 research outputs found
Decision making with both diversity supporting and opposing membership information
Online big data provides large amounts of decision information
to decision makers, but supporting and opposing information are
present simultaneously. Dual hesitant fuzzy sets (DHFSs) are useful
models for exactly expressing the membership degree of both
supporting and opposing information in decision making.
However, the application of DHFSs requires an improved distance
measure. This paper aims to improve distance measure models
for DHFSs and apply the new distance models to generate a technique
for order preference by similarity to an ideal solution
(TOPSIS) method for multiple attribute decision making (MADM)
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
A New Similarity Measure between Intuitionistic Fuzzy Sets and Its Application to Pattern Recognition
As a generation of ordinary fuzzy set, the concept of intuitionistic fuzzy set (IFS), characterized both by a membership degree and by a nonmembership degree, is a more flexible way to cope with the uncertainty. Similarity measures of intuitionistic fuzzy sets are used to indicate the similarity degree between intuitionistic fuzzy sets. Although many similarity measures for intuitionistic fuzzy sets have been proposed in previous studies, some of those cannot satisfy the axioms of similarity or provide counterintuitive cases. In this paper, a new similarity measure and weighted similarity measure between IFSs are proposed. It proves that the proposed similarity measures satisfy the properties of the axiomatic definition for similarity measures. Comparison between the previous similarity measures and the proposed similarity measure indicates that the proposed similarity measure does not provide any counterintuitive cases. Moreover, it is demonstrated that the proposed similarity measure is capable of discriminating difference between patterns
Modified EDAS Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-valued Intuitionistic Fuzzy Information
The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the
intuitionistic fuzzy sets combines the classical decision method is in its
research and application is attracting attention. After comparative analysis,
there are multiple classical methods with IVIFSs information have been applied
into many practical issues. In this paper, we extended the classical EDAS
method based on cumulative prospect theory (CPT) considering the decision
makers (DMs) psychological factor under IVIFSs. Taking the fuzzy and uncertain
character of the IVIFSs and the psychological preference into consideration,
the original EDAS method based on the CPT under IVIFSs (IVIF-CPT-MABAC) method
is built for MAGDM issues. Meanwhile, information entropy method is used to
evaluate the attribute weight. Finally, a numerical example for project
selection of green technology venture capital has been given and some
comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some
comparison analysis and sensitivity analysis are applied to prove this new
methods effectiveness and stability.Comment: 48 page
Investigation on soft computing techniques for airport environment evaluation systems
Spatial and temporal information exist widely in engineering fields, especially
in airport environmental management systems. Airport environment is influenced
by many different factors and uncertainty is a significant part of the
system. Decision support considering this kind of spatial and temporal information
and uncertainty is crucial for airport environment related engineering
planning and operation. Geographical information systems and computer aided
design are two powerful tools in supporting spatial and temporal information
systems. However, the present geographical information systems and computer
aided design software are still too general in considering the special features in
airport environment, especially for uncertainty. In this thesis, a series of parameters
and methods for neural network-based knowledge discovery and training
improvement are put forward, such as the relative strength of effect, dynamic
state space search strategy and compound architecture. [Continues.
Several Similarity Measures of Neutrosophic Sets
Smarandache (1995) defined the notion of neutrosophic sets, which is a generalization of Zadeh's fuzzy set and Atanassov's intuitionistic fuzzy set. In this paper, we first develop some similarity measures of neutrosophic sets. We will present a method to calculate the distance between neutrosophic sets (NS) on the basis of the Hausdorff distance. Then we will use this distance to generate a new similarity measure to calculate the degree of similarity between NS. Finally we will prove some properties of the proposed similarity measures
Several Similarity Measures of Neutrosophic Sets
Smarandache (1995) defined the notion of neutrosophic sets, which is a generalization of Zadeh's fuzzy set and Atanassov's intuitionistic fuzzy set. In this paper, we first develop some similarity measures of neutrosophic sets. We will present a method to calculate the distance between neutrosophic sets (NS) on the basis of the Hausdorff distance. Then we will use this distance to generate a new similarity measure to calculate the degree of similarity between NS. Finally we will prove some properties of the proposed similarity measures
Several Similarity Measures of Neutrosophic Sets
Smarandache (1995) defined the notion of neutrosophic sets, which is a generalization of Zadeh's fuzzy set and Atanassov's intuitionistic fuzzy set. In this paper, we first develop some similarity measures of neutrosophic sets. We will present a method to calculate the distance between neutrosophic sets (NS) on the basis of the Hausdorff distance. Then we will use this distance to generate a new similarity measure to calculate the degree of similarity between NS. Finally we will prove some properties of the proposed similarity measures
Several Similarity Measures of Neutrosophic Sets
Smarandache (1995) defined the notion of neutrosophic sets, which is a generalization of Zadeh's fuzzy set and Atanassov's intuitionistic fuzzy set. In this paper, we first develop some similarity measures of neutrosophic sets. We will present a method to calculate the distance between neutrosophic sets (NS) on the basis of the Hausdorff distance. Then we will use this distance to generate a new similarity measure to calculate the degree of similarity between NS. Finally we will prove some properties of the proposed similarity measures
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