Fundamentals of Fuzzy Information Measures

2016 ◽  
pp. 1-22 ◽  
Author(s):  
Anshu Ohlan ◽  
Ramphul Ohlan
Keyword(s):  
Fuzzy Information ◽  
Information Measures

The distance measures and cross-entropy based on complex fuzzy sets and their application in decision making

2020 ◽  
Vol 39 (3) ◽  
pp. 3351-3374
Author(s):  
Peide Liu ◽  
Zeeshan Ali ◽  
Tahir Mahmood
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Similarity Measures ◽  
Decision Makers ◽  
Cross Entropy ◽  
Distance Measures ◽  
Fuzzy Information ◽  
Information Measures ◽  
Entropy Measures ◽  
Magdm Problems

The information measures (IMs) of complex fuzzy information are very useful tools in the areas of machine learning and decision making. In some multi-attribute group decision making (MAGDM) problems, the decision makers can make a decision mostly according to IMs such as similarity measures (SMs), distance measures (DIMs), entropy measures (EMs) and cross-entropy measures (C-EMs) in order to choose the best one. However, the relation between C-EMs and DIMs in the environment of complex fuzzy sets (CFSs) has not been developed and verified. In this manuscript, the notions of DIMs and C-EMs in the environment of CFSs are investigated and the relation between DIMs and EMs in the environment of CFSs is also discussed. The complex fuzzy discrimination measures (CFDMs), the complex fuzzy cross-entropy measures (CFC-EMs), and the symmetry complex fuzzy cross-entropy measures (SCFC-EMs) are proposed. We also examined that the C-EMs satisfied all the conditions of DIMs, and finally proved that C-EMs including CFC-EMs were also a DIMs. In last, we used some practical examples to illustrate the validity and superiority of the proposed method by comparing with other existing methods.

scholarly journals Comparative Study of Generalized Quantitative-Qualitative Inaccuracy Fuzzy Measures for Noiseless Coding Theorem and 1:1 Codes

2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
H. D. Arora ◽  
Anjali Dhiman
Keyword(s):  
Information Theory ◽  
Data Compression ◽  
Error Correction ◽  
Coding Theory ◽  
Fuzzy Information ◽  
Fuzzy Measures ◽  
Information Measures ◽  
Codeword Length ◽  
Engineering Mathematics ◽  
The Relationship

In coding theory, we study various properties of codes for application in data compression, cryptography, error correction, and network coding. The study of codes is introduced in Information Theory, electrical engineering, mathematics, and computer sciences for the transmission of data through reliable and efficient methods. We have to consider how coding of messages can be done efficiently so that the maximum number of messages can be sent over a noiseless channel in a given time. Thus, the minimum value of mean codeword length subject to a given constraint on codeword lengths has to be founded. In this paper, we have introduced mean codeword length of orderαand typeβfor 1:1 codes and analyzed the relationship between average codeword length and fuzzy information measures for binary 1:1 codes. Further, noiseless coding theorem associated with fuzzy information measure has been established.

scholarly journals Two New Parametric Generalized R?Norm Fuzzy Information Measures

2014 ◽  
Vol 93 (13) ◽  
pp. 22-27 ◽  
Author(s):  
Vijay PrakashTomar ◽  
Anshu Gahlawat
Keyword(s):  
Fuzzy Information ◽  
Information Measures

scholarly journals Information measures for generalized hesitant fuzzy information

2016 ◽  
Vol 26 (1) ◽  
pp. 76-81
Author(s):  
Jin Han Park ◽  
Hee Eun Kwark ◽  
Young Chel Kwun
Keyword(s):  
Fuzzy Information ◽  
Information Measures
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