On depth-based fuzzy trimmed means and a notion of depth specifically defined for fuzzy numbers

Author(s):  
Beatriz Sinova
Keyword(s):  
2020 ◽  
Vol 7 (1) ◽  
pp. 72-83
Author(s):  
Alevtina Yu. Shatalova ◽  
◽  
Igor V. Shevchenko ◽  
Boureima Bamadio ◽  
Konstantin A. Lebedev ◽  
...  

2020 ◽  
Vol S (1) ◽  
pp. 295-298
Author(s):  
Stephen Dinagar D. ◽  
Manvizhi M.
Keyword(s):  

2018 ◽  
Vol 9 (11) ◽  
pp. 1717-1727
Author(s):  
Ajay Minj ◽  
Pathinathan T.

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 474 ◽  
Author(s):  
Lazaros Moysis ◽  
Christos Volos ◽  
Sajad Jafari ◽  
Jesus M. Munoz-Pacheco ◽  
Jacques Kengne ◽  
...  

A modification of the classic logistic map is proposed, using fuzzy triangular numbers. The resulting map is analysed through its Lyapunov exponent (LE) and bifurcation diagrams. It shows higher complexity compared to the classic logistic map and showcases phenomena, like antimonotonicity and crisis. The map is then applied to the problem of pseudo random bit generation, using a simple rule to generate the bit sequence. The resulting random bit generator (RBG) successfully passes the National Institute of Standards and Technology (NIST) statistical tests, and it is then successfully applied to the problem of image encryption.


Author(s):  
Raissa T. Vieira ◽  
Carlos Eduardo de Oliveira Chierici ◽  
Carolina T. Ferraz ◽  
Adilson Gonzaga

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 468
Author(s):  
Krzysztof Piasecki ◽  
Anna Łyczkowska-Hanćkowiak

In general, the present value (PV) concept is ambiguous. Therefore, behavioural factors may influence on the PV evaluation. The main aim of our paper is to propose some method of soft computing PV evaluated under the impact of behavioural factors. The starting point for our discussion is the notion of the Behavioural PV (BPV) defined as an imprecisely real-valued function of distinguished variables which can be evaluated using objective financial knowledge or subjective behavioural premises. In our paper, a BPV is supplemented with a forecast of the asset price closest to changes. Such BPV is called the oriented BPV (O-BPV). We propose to evaluate an O-BPV by oriented fuzzy numbers which are more useful for portfolio analysis than fuzzy numbers. This fact determines the significance of the research described in this article. O-BPV may be applied as input signal for systems supporting invest-making. We consider here six cases of O-BPV: overvalued asset with the prediction of a rise in its price, overvalued asset with the prediction of a fall in its price, undervalued asset with the prediction of a rise in its price, undervalued asset with the prediction of a fall in its price, fully valued asset with the prediction of a rise in its rice and fully valued asset with the prediction of a fall in its rice. All our considerations are illustrated by numerical examples. Presented examples show the way in which we transform superposition of objective market knowledge and subjective investment opinion into simple return rate.


2021 ◽  
pp. 1-11
Author(s):  
Hacer Yumurtacı Aydoğmuş ◽  
Eren Kamber ◽  
Cengiz Kahraman

The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness.


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