Soft computing fuzzy set through knn−ML to identify islanding state of integrated electrical grid at different operational events

Author(s):  
K. Harinadha Reddy
Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1351
Author(s):  
Qingsong Mao ◽  
Huan Huang

Wu introduced the interval range of fuzzy sets. Based on this, he defined a kind of arithmetic of fuzzy sets using a gradual number and gradual sets. From the point of view of soft computing, this definition provides a new way of handling the arithmetic operations of fuzzy sets. The interval range is an important characterization of a fuzzy set. The interval range is also useful for analyses and applications of arithmetic. In this paper, we present general conclusions on crucial problems related to interval ranges of fuzzy sets induced by this arithmetic. These conclusions indicate that the corresponding conclusions in previous works should be modified: firstly, we give properties of the arithmetic and the composites of finite arithmetic. Then, we discuss the relationship between the domain of a gradual set and the range of its induced fuzzy set, and the relationship between the domain of a gradual set and the interval range of its induced fuzzy set. Based on the above results, we present the relationship between the intersection of the interval ranges of a group of fuzzy sets and the interval ranges of their resulting fuzzy sets obtained by compositions of finite arithmetic. Furthermore, we construct examples to show that even under conditions stronger than in previous work, there are still various possibilities in the relationship between the intersection of interval ranges of a group of fuzzy sets and the ranges of their resulted fuzzy sets, and there are still various possibilities in the relationship between the intersection of the interval ranges of a group of fuzzy sets and the interval ranges of their resulting fuzzy sets.


2021 ◽  
Author(s):  
Augustine Ejegwa ◽  
Idoko Charles Onyeke

Abstract Fermatean fuzzy set is a competent tool in curbing indeterminacy embedded in soft computing. Fermatean fuzzy set generalizes both intuitionistic fuzzy sets and Pythagorean fuzzy sets in an effective way to handle imprecision by expanding the spatial scope of Pythagorean/intuitionistic fuzzy sets. Distance measure has become an integral aspect of utilizing generalized fuzzy sets in soft computing. In this paper, a novel distance measure between Fermatean fuzzy sets is introduced with a better and reliable output. Some properties of the proposed distance measure are characterized. It is demonstrated that the new distance measure between Fermatean fuzzy sets is more reliable than the existing Fermatean fuzzy distance measure. In addition, it is shown that Fermatean fuzzy set is more equipped to curb imprecision than Pythagorean/intuitionistic fuzzy sets. In terms of application, the new Fermatean fuzzy distance measure is utilized in executing students’ admission process using an algorithmic approach implemented by a programming language to enhance accuracy and ease of computations.


2015 ◽  
Author(s):  
Balamati Choudhury ◽  
Rakesh Mohan Jha
Keyword(s):  

1978 ◽  
Vol 23 (5) ◽  
pp. 319-320
Author(s):  
LEWIS WOLFGANG BRANDT
Keyword(s):  

1990 ◽  
Vol 29 (04) ◽  
pp. 386-392 ◽  
Author(s):  
R. Degani ◽  
G. Bortolan

AbstractThe main lines ofthe program designed for the interpretation of ECGs, developed in Padova by LADSEB-CNR with the cooperation of the Medical School of the University of Padova are described. In particular, the strategies used for (i) morphology recognition, (ii) measurement evaluation, and (iii) linguistic decision making are illustrated. The main aspect which discerns this program in comparison with other approaches to computerized electrocardiography is its ability of managing the imprecision in both the measurements and the medical knowledge through the use of fuzzy-set methodologies. So-called possibility distributions are used to represent ill-defined parameters as well as threshold limits for diagnostic criteria. In this way, smooth conclusions are derived when the evidence does not support a crisp decision. The influence of the CSE project on the evolution of the Padova program is illustrated.


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