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- Information fusion (3)
- DSmT (2)
- Belief functions (1)
- Conjunctive rule (1)
- Counter-examples to Dempster rule (1)
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- Counterexamples to Conjunctive rule (1)
- Dempster rule (1)
- Google colaboratory (1)
- Integrity constraints (1)
- Interval valued neutrosophic graph; Generalized Interval valued neutrosophic graphs of first type; Matrix representation. (1)
- K-NN; Fuzzy k-NN; neutrosophic sets; data classification (1)
- Neutrosophic computing (1)
- Neutrosophic logic (1)
- Neutrosophic number (1)
- PCR5 fusion rules (1)
- Sympy (1)
Articles 1 - 6 of 6
Full-Text Articles in Computational Engineering
Neutrosophic Computing With Sympy (Computación Neutrosófica Mediante Sympy ), Maykel Leyva-Vazquez, Florentin Smarandache
Neutrosophic Computing With Sympy (Computación Neutrosófica Mediante Sympy ), Maykel Leyva-Vazquez, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
In this article the concept of neutrosophic number is presented. Jupyter through Google Colaboratory is introduced for calculations. The Sympy library is used to perform the process of neutrosophic computation. Systems of linear neutrosóficas equations are solved by means of the symbolic computation in python. A case study was developed for the determination of vehicular traffic with indeterminacy. As future works are the development of new applications in different areas of engineering and science.
Ns-K-Nn: Neutrosophic Set-Based K-Nearest Neighbors Classifier, Florentin Smarandache, Yaman Akbulut, Abdulkadir Sengur, Yanhui Guo
Ns-K-Nn: Neutrosophic Set-Based K-Nearest Neighbors Classifier, Florentin Smarandache, Yaman Akbulut, Abdulkadir Sengur, Yanhui Guo
Branch Mathematics and Statistics Faculty and Staff Publications
k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametric supervised classifier. It aims to determine the class label of an unknown sample by its k-nearest neighbors that are stored in a training set. The k-nearest neighbors are determined based on some distance functions. Although k-NN produces successful results, there have been some extensions for improving its precision. The neutrosophic set (NS) defines three memberships namely T, I and F. T, I, and F shows the truth membership degree, the false membership degree, and the indeterminacy membership degree, respectively. In this paper, the NS …
Generalized Interval Valued Neutrosophic Graphs Of First Type, Florentin Smarandache, Said Broumi, Mohamed Talea, Assia Bakali, Ali Hassan
Generalized Interval Valued Neutrosophic Graphs Of First Type, Florentin Smarandache, Said Broumi, Mohamed Talea, Assia Bakali, Ali Hassan
Branch Mathematics and Statistics Faculty and Staff Publications
In this paper, motivated by the notion of generalized single valued neutrosophic graphs of first type, we defined a new neutrosophic graphs named generalized interval valued neutrosophic graphs of first type (GIVNG1) and presented a matrix representation for it and studied few properties of this new concept. The concept of GIVNG1 is an extension of generalized fuzzy graphs (GFG1) and generalized single valued neutrosophic of first type (GSVNG1).
Importance Of Sources Using The Repeated Fusion Method And The Proportional Conflict Redistribution Rules #5 And #6, Florentin Smarandache, Jean Dezert
Importance Of Sources Using The Repeated Fusion Method And The Proportional Conflict Redistribution Rules #5 And #6, Florentin Smarandache, Jean Dezert
Branch Mathematics and Statistics Faculty and Staff Publications
We present in this paper some examples of how to compute by hand the PCR5 fusion rule for three sources, so the reader will better understand its mechanism. We also take into consideration the importance of sources, which is different from the classical discounting of sources.
Examples Where The Conjunctive And Dempster’S Rules Are Insensitive, Florentin Smarandache, Jean Dezert, Valeri Kroumov
Examples Where The Conjunctive And Dempster’S Rules Are Insensitive, Florentin Smarandache, Jean Dezert, Valeri Kroumov
Branch Mathematics and Statistics Faculty and Staff Publications
In this paper we present several counter-examples to the Conjunctive rule and to Dempster rule of combinations in information fusion.
Extended Pcr Rules For Dynamic Frames, Florentin Smarandache, Jean Dezert
Extended Pcr Rules For Dynamic Frames, Florentin Smarandache, Jean Dezert
Branch Mathematics and Statistics Faculty and Staff Publications
In most of classical fusion problems modeled from belief functions, the frame of discernment is considered as static. This means that the set of elements in the frame and the underlying integrity constraints of the frame are fixed forever and they do not change with time. In some applications, like in target tracking for example, the use of such invariant frame is not very appropriate because it can truly change with time. So it is necessary to adapt the Proportional Conflict Redistribution fusion rules (PCR5 and PCR6) for working with dynamical frames. In this paper, we propose an extension of …