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pro vyhledávání: '"Zi Chun Chen"'
Autor:
Haifeng Song, Zi-chun Chen
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 14, Iss 1 (2021)
As an extension of hesitant fuzzy set, the probabilistic hesitant fuzzy set (PHFS) can more accurately express the initial decision information given by experts, thus the decision method based on PHFS is more true and reliable. In this paper, multi-a
Externí odkaz:
https://doaj.org/article/114a11043b3b4e6cb22bf8270ad6c6ba
Autor:
Gen Bin Huang, Zi Chun Chen, Luo Yuan Cao, Jing Yang, Yong Tong Xin, Xian Guo Fu, Qi Fang Lin, Long Teng Yao
Publikováno v:
Journal of Clinical Neurology (Seoul, Korea)
BACKGROUND AND PURPOSE Five single-nucleotide polymorphisms (SNPs) (rs4379368, rs10504861, rs10915437, rs12134493 and rs13208321) were recently identified in a Western population with migraine. These migraine-associated SNPs have not been evaluated i
Publikováno v:
2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC).
Attribute reduction is one of the most important areas of research in rough sets. This paper mainly discusses the fuzzy approximate distribution reduction problem of hesitant fuzzy decision tables from the perspective of dominant fuzzy rough sets. Fi
Autor:
Zi-Chun Chen, 陳姿君
98
Since a color image usually contains a number of various objects, the main purpose of the color image segmentation is to clearly divide a color image into several objects or clusters where each object contains pixels that are similar or deeme
Since a color image usually contains a number of various objects, the main purpose of the color image segmentation is to clearly divide a color image into several objects or clusters where each object contains pixels that are similar or deeme
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/82e89v
Publikováno v:
Int. Conf. Interaction Sciences
Thresholding is an important technology for image segmentation. Before we get the segmentation thresholds, most segmentation technologies need to set many parameters. This paper presents a method to automatically determine how many thresholds should