• Corpus ID: 54829971

A Distance Model of Intuitionistic Fuzzy Cross Entropy to Solve Preference Problem on Alternatives

  title={A Distance Model of Intuitionistic Fuzzy Cross Entropy to Solve Preference Problem on Alternatives},
  author={Mei Li and ChongWu},
In the field of decision-making, for the multiple attribute decision-making problem with the partially unknown attribute weights, the evaluation information in the form of the intuitionistic fuzzy numbers, and the preference on alternatives, this paper proposes a comprehensive decision model based on the intuitionistic fuzzy cross entropy distance and the grey correlation analysis. The creative model can make up the deficiency that the traditional intuitionistic fuzzy distance measure is easy… 

Tables from this paper

Kullback-Leibler Distance Based Generalized Grey Target Decision Method With Index and Weight Both Containing Mixed Attribute Values
A generalized grey target decision method with index and weight both containing mixed attribute values based on Kullback-Leibler (K-L) distance is proposed with its effectiveness of converting the uncertain weights into the certain weights and the accurate results comparing with other decision-making methods.
Cloud service reliability assessment approach based on multi-valued neutrosophic cross-entropy and entropy measures
A novel extended VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method based on entropy and cross-entropy measures is developed to address the decision-making problems when information about criteria weights is absolutely unknown.
Explicit methods for attribute weighting in multi-attribute decision-making: a review study
A categorization of existing methodologies is proposed, which goes beyond the current taxonomy (subjective, objective, hybrid) and critically discusses the explicit weighting methods (which are closely related to the subjective ones).
Generalized Grey Target Decision Method for Mixed Attributes Based on Kullback-Leibler Distance
A novel generalized grey target decision method for mixed attributes based on Kullback-Leibler (K-L) distance is proposed and the final decision is based on the integrated value on a bigger the better basis.
Evaluating Algorithms for the Service Quality of Wireless SensorNetworks Based on Interval-Valued Intuitionistic Fuzzy EDAS and CRITIC Methods
The classical EDAS method will be extended to interval-valued intuitionistic fuzzy sets (IVIFSs) to address some MAGDM issues and an empirical application for evaluating the service quality of wireless sensor networks is given.
Syndicated venture capital portfolio companies selection: a fuzzy inference system – agent-based approach
In this paper, start-up portfolio selection is simulated which is more similar to real-world problems rather than other research, and preferences of start-ups and their interaction with investors are considered.
Improved LS-SVM Method for Flight Data Fitting of Civil Aircraft Flying at High Plateau
The fitting results show that the improved least squares support vector machines machine learning model can fit and supplement the missing QAR data in the plateau area through historical flight data to effectively meet application needs.
A Venture Capital Recommendation Algorithm based on Heterogeneous Information Network
This paper proposes VC-Recom, a recommendation algorithm based on heterogeneous information network, which helps investment companies find suitable startup projects, and experimental results show that the proposed algorithm can produce more effective recommendation results for investment firms compared with other methods.


Interval-valued intuitionistic fuzzy continuous cross-entropy and its application in multi-attribute decision-making
The concept of the interval-valued intuitionistic fuzzy continuous cross-entropy under the intervalvalued intuitionism fuzzy environment, which is based on the COWA operator, is presented, aiming that the information about attribute weights is completely unknown.
An Intuitionistic Fuzzy Multi-attribute Decision-making Method with Preference on Alternatives
An intuitionistic fuzzy multi-attribute decision-making method with preference on alternatives is obtained and a practical example is given to illustrate that the developed method is effective and reasonable.
A Triangular Fuzzy Number Multi-attribute Decision-making Method with Preference Information on Alternatives
A programming model for obtaining attribute weight based on deviation between synthesizing values and preference values on alternatives is solved, based on the possibility degree formula of triangular fuzzy numbers and priority formula of complementary judgment matrix.
Study on Method for Triangular Fuzzy Number-Based Multi-Attribute Decision Making With Preference Information on Alternatives
  • Xu Ze
  • Computer Science
  • 2002
A linear programming model is established, and the attribute weights are derived by solving this model, and based on a possibility degree formula for comparing two triangular fuzzy numbers and a formula for priorities of complementary judgement matrix, a priority method for alternatives is presented.
TOPSIS-Based Nonlinear-Programming Methodology for Multiattribute Decision Making With Interval-Valued Intuitionistic Fuzzy Sets
  • Dengfeng Li
  • Computer Science
    IEEE Transactions on Fuzzy Systems
  • 2010
A nonlinear-programming methodology based on the technique for order preference by similarity to ideal solution to solve multiattribute decision-making (MADM) problems with both ratings of alternatives on attributes and weights of attributes expressed with IVIF sets is developed.
Multiple-Attribute Group Decision Making With Different Formats of Preference Information on Attributes
  • Zeshui Xu
  • Economics, Computer Science
    IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
  • 2007
A goal-programming model is established to integrate the expected decision matrix and all three different uncertain-preference formats from which the attribute weights and the overall attribute values of alternatives can be obtained and can avoid losing and distorting the given objective and subjective decision information in the process of information integration.