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Article type: Research Article
Authors: Zhang, Yingying
Affiliations: College of Fine Art and Design, Shenyang Normal University, Shenyang, Liaoning 110034, China | E-mail: [email protected]
Correspondence: [*] Corresponding author: College of Fine Art and Design, Shenyang Normal University, Shenyang, Liaoning 110034, China. E-mail: [email protected].
Abstract: The environmental design major has certain practical characteristics. In the teaching process, it is necessary to effectively combine practical methods and theoretical knowledge in order to improve the overall quality and efficiency of education to a certain extent. The most important training measure currently is project-based teaching method, which has also been recognized by many researchers. The environmental design majors teaching quality evaluation is a classical multiple-attribute group decision-making (MAGDM). Recently, the Taxonomy has been used to cope with MAGDM problems. The interval-valued Pythagorean fuzzy sets (IVPFSs) are useful tools to depict uncertainty in MAGDM. This paper use Taxonomy method to solve MAGDM with IVPFSs. Firstly, the concepts of IVPFSs are presented. Then, the classical Taxonomy method is used to solve MAGDM with IVPFSs. Finally, a numerical example for environmental design majors teaching quality evaluation is proposed and a comparative analysis is also given to show the developed approach. The main study motivations of built paper are outlined: (1) the Taxonomy method is extended to IVPFSs; (2) the score function of IVPFSs and information entropy method is used to derive the attribute weights; (3) the interval-valued Pythagorean fuzzy Taxonomy (IVPF-Taxonomy) method is built to deal with MAGDM; (4) a case study about environmental design majors teaching quality evaluation is given to show the built method; (5) some comparative analysis are given to show the rationality of IVPF-Taxonomy method.
Keywords: Multipleattribute group decisionmaking (MAGDM), interval-valued pythagorean fuzzy sets (IVPFSs), taxonomy method, teaching quality evaluation
DOI: 10.3233/KES-230124
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 27, no. 3, pp. 289-301, 2023
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