Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Le Sheng Jin"'
Interval Type Interval and Cognitive Uncertain Information in Information Fusion and Decision Making
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 16, Iss 1, Pp 1-9 (2023)
Abstract More uncertainty can be obtained when real numbers are extended to intervals. The two new concepts proposed in this work are the natural extensions of cognitive interval information and cognitive uncertain information with real numbered valu
Externí odkaz:
https://doaj.org/article/4a8cda2540084ff3b9b01622cea40550
Autor:
Cheng Zhu, Er Zi Zhang, Zhen Wang, Ronald R. Yager, Zhi Song Chen, Le Sheng Jin, Zhen-Song Chen
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 14, Iss 1 (2020)
Most of the evaluation problems are comprehensive and with ever-increasingly more uncertainties. By quantifying the involved uncertainties, Basic Uncertain Information can both well handle and merge those uncertainties in the input information. This
Externí odkaz:
https://doaj.org/article/a0d1b6f1fe0040639b120b00be34875b
Publikováno v:
International Journal of Computational Intelligence Systems. 15
Basic uncertain information is a newly proposed normative formulation to express and model uncertain information. This study further generalizes this concept by introducing the concept of refined interval of discourse in which the true value is known
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63a3b9179302c9439060cf9e5d7102ba
https://doi.org/10.1007/s44196-022-00066-9
https://doi.org/10.1007/s44196-022-00066-9
Autor:
Ya-Qiang Xu, Le-Sheng Jin, Zhen-Song Chen, Ronald R. Yager, Jana Špirková, Martin Kalina, Surajit Borkotokey
Publikováno v:
Mathematics; Volume 10; Issue 4; Pages: 572
This paper elaborates the different methods to generate normalized weight vector in multi-criteria decision-making where the given information of both criteria and inputs are uncertain and can be expressed by basic uncertain information. Some general
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f615399cb142dc02ba49e7f7cabe8430
https://doi.org/10.3390/math10040572
https://doi.org/10.3390/math10040572
Publikováno v:
International Journal of Intelligent Systems. 33:1283-1300
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5de9424f3df3a53d9c78cdd9d31da1af
https://doi.org/10.1002/int.21982
https://doi.org/10.1002/int.21982
Autor:
Zhi Song Chen, Zhen-Song Chen, Ronald R. Yager, Cheng Zhu, Er Zi Zhang, Zhen Wang, Le Sheng Jin
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 14, Iss 1 (2020)
Most of the evaluation problems are comprehensive and with ever-increasingly more uncertainties. By quantifying the involved uncertainties, Basic Uncertain Information can both well handle and merge those uncertainties in the input information. This
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de72973dd65447ca781f33c9e43b0c76
https://doi.org/10.2991/ijcis.d.201109.002
https://doi.org/10.2991/ijcis.d.201109.002
Autor:
Zhen Wang, Le Sheng Jin
Publikováno v:
Science Journal of Education. 4:175
Evaluation functions are very crucial in educational comprehensive evaluation. This study summarizes some classical evaluation functions and shows their usage in Pedagogic evaluation applications. The study also presents and illustrates some hybrid e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9dd66e57cfa8825606add08d6b901642
https://doi.org/10.11648/j.sjedu.20160406.12
https://doi.org/10.11648/j.sjedu.20160406.12