Abstract: In this paper, similar to the extension from intuitionistic fuzzy numbers (IFNs) to neutrosophic numbers (NNs), we propose the normal neutrosophic numbers (NNNs) based on the normal intuitionistic fuzzy numbers (NIFNs) to handle the incompleteness, indeterminacy and inconsistency of the evaluation information. In addition, because Heronian mean (HM) operators can consider capture the ...

Heronianmean (HM) has the characteristic of capturing the correlations of the aggregated arguments and the neutrosophic set can express the incomplete, indeterminate and inconsistent information, in this paper, we applied the Heronian mean to the neutrosophic set, and proposed some Heronian mean operators. Firstly, we presented some operational laws and their properties of single valued neutros...

We model document summarization as a nonlinear 0-1 programming problem where an objective function is defined as Heronian mean of the objective functions enforcing the coverage and diversity. The proposed model implemented on a multi-document summarization task. Experiments on DUC2001 and DUC2002 datasets showed that the proposed model outperforms the other summarization methods. Index Terms – ...

The main focus of this paper is to investigate intuitionistic linguistic information fusion based on Heronian mean. Two new intuitionistic linguistic aggregation operators called intuitionistic linguistic generalized Heronian mean (ILGHM) and intuitionistic linguistic generalized weighted Heronian mean (ILGWHM) operators, are introduced. The ILGHM and ILGWHM operators are characterized by the a...

In this paper an adaptable algorithm for simulating CNN arrays is implemented using various RK-fourth order means such as Arithmetic Mean [AM], Centroidal Mean [CM], Harmonic Mean [HM], Contra Harmonic Mean [CoM], Heronian Mean [HeM], Geometric Mean [GM] and Root Mean Square [RMS] also, it is compared with RK-fourth order embedded means such as the RK-Embedded Heronian Mean, RK-Embedded Centroi...

This paper introduces new similarity classifiers using the Heronian mean, and the generalized Heronian mean operators. We examine the use of these operators at the aggregation step within the similarity classifier. The similarity classifier was earlier studied with other operators, in particular with an arithmetic mean, generalized mean, OWA operators, and many more. The two classifiers here ar...