caa a22 4500 606159630 CHVBK 20210128100625.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00521-014-1648-3 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1648-3 NECM: Neutrosophic evidential c -means clustering algorithm [Elektronische Daten] [Yanhui Guo, Abdulkadir Sengur] A new clustering algorithm, neutrosophic evidential c-means (NECM) is introduced based on the neutrosophic set (NS) and the evidence theory. The clustering analysis is formulated as a constrained minimization problem, whose solution depends on an objective function. In the objective function of NECM, two new types of rejection have been introduced using NS theory: the ambiguity rejection which concerns the patterns lying near the class boundaries, and the distance rejection dealing with patterns that are far away from all the classes. A belief function evidence theory is employed to make the final decision, and it is defined using the concept of Dezert-Smarandache theory of plausible and paradoxical reasoning, which is a natural extension of the classical Dempster-Shafer theory. A variety of experiments were conducted using synthetic and real data sets. The results are promising and compared favorably with the results from the evidential c-means algorithm on the same data sets. We also applied the proposed method into the image segmentation. The experimental results show that the proposed algorithm can be considered as a promising tool for data clustering and image processing. The Natural Computing Applications Forum, 2014 Data clustering nationallicence Fuzzy c -means clustering nationallicence Neutrosophic set nationallicence Belief function nationallicence Image segmentation nationallicence Guo Yanhui School of Science, Saint Thomas University, 33054, Miami Gardens, FL, USA aut Sengur Abdulkadir Department of Computer Software Engineering, Firat University, 23119, Elazig, Turkey aut Neural Computing and Applications Springer London 26/3(2015-04-01), 561-571 0941-0643 26:3<561 2015 26 521 https://doi.org/10.1007/s00521-014-1648-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1648-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Guo Yanhui School of Science, Saint Thomas University, 33054, Miami Gardens, FL, USA aut NATIONALLICENCE 700 1- Sengur Abdulkadir Department of Computer Software Engineering, Firat University, 23119, Elazig, Turkey aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/3(2015-04-01), 561-571 0941-0643 26:3<561 2015 26 521