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This paper presents a work about palm print recognition using fuzzy entropy. A number of schemes have been proposed to combine the fuzzy set theory and its application to the entropy concept for modelling a palm print recognition system. The measure of uncertainty is adopted as a measure of information. Hence, the measures of fuzziness are known as fuzzy information measures. The measure of information...
Information theory was introduced by Shannon in 1948 and it includes the study of uncertainty measures. Analogous to information theory which is based on probability theory fuzzy set theory was developed by Zadeh in 1965 which is a mechanism to manage uncertainty. The pedestal for present study is information theory and fuzzy set theory which is termed as fuzzy information theory. In this paper a...
In this paper, a new attempt has been made using fuzzy set to construct intuitionistic fuzzy set basing on fuzzy entropy. A new intuitionistic fuzzy set generator is defined, which obtained hesitation degree by applying so-called ‘complement’ to membership. The relationship between fuzzy entropy and hesitation degree of intuitionistic fuzzy set is discussed. The method to calculate hesitation degree...
A fuzzy approach to assess service satisfaction values of retailers is discussed in this paper, which has been developed from fuzzy assessment methods and applied to questionnaire analysis of retailers' service satisfaction. Subjective judgments are often vague and it is not easy for retailers to express the satisfaction of service quality using an exact numerical value, and suggest the necessity...
A new distance measure is defined for vague sets, and then the corresponding measure formula for the fuzzy entropy of vague sets is proposed. Finally, comparison of the existing formulae and our one shows that our formula is more reasonable.
Fuzzy entropy and similarity measure were used to measure the information of data as real value. In order to calculate the certainty or uncertainty fuzzy entropy and similarity measure are designed and proved. Obtained measures were applied to the calculating process and discussed. Extension of data quantification results to decision making and fuzzy game theory were also discussed.
The rough fuzzy sets (RFS) is a combination granular computing model with rough sets and fuzzy sets. Its uncertainty includes roughess, rough entropy, fuzziness and fuzzy entropy, etc.. In this paper, the changes of roughness, cut-set and fuzziness are discussed according to the knowledge granularity in different knowledge granularity levels in apporiximation spaces of rough fuzzy sets. Hence, the...
We survey the relation property of fuzzy entropy measure and similarity measure. Each measure represents measure of data uncertainty and degree of similarity between comparative data group. By the analysis of one-to-one correspondence, distance measure and similarity measure have been expressed by the complementary characteristics. We construct similarity measure using distance measure, and verification...
Portfolio recommendation in stock market is complex, especially when the required data are vague. In order to evaluate the stocks and recommend the high priority of them to the customers, it is necessary to rank the stocks based on the criteria which is obtained from literature. Since in this paper the stocks score were presented by fuzzy number, fuzzy entropy method is used to calculate the stock...
Dataset dimensionality is undoubtedly the single most significant obstacle which exasperates any attempt to apply effective computational intelligence techniques to problem domains. In order to address this problem a technique which reduces dimensionality is employed prior to the application of any classification learning. Such feature selection (FS) techniques attempt to select a subset of the original...
Fuzzy entropy is an important concept of intuitionistic fuzzy sets (IFSs). In this paper, the resources of the entropy of an intuitionistic fuzzy set are analyzed. It is pointed out that the fuzzy entropy of an IFS comes from uncertainty and unknown information. A new formula is proposed and some numerical examples are given to compare it with the existing methods. It is found that conditions proposed...
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