An improved CLVA method for evaluating the endurance quality level of young male basketball players with 2-tuple linguistic neutrosophic information

Article type: Research Article

Authors: Zhang, Haibo^{; *}

Affiliations: Shanxi Vocational College of Tourism, Taiyuan, Shanxi, China

Correspondence: [*] Corresponding author. Haibo Zhang. E-mails: [email protected]. and [email protected].

Abstract: For a long time, the level of endurance quality of our male basketball athletes is not high, and there is a gap with the strongest countries in Europe and America. The former head coach of Chinese men’s basketball team diagnosed the biggest problem of Chinese men’s basketball team and Chinese youth men’s basketball team is the poor quality of endurance. It is especially important to strengthen the endurance training of our basketball players and improve their endurance level. However, from the current situation, the teams in the training due to the lack of standards for endurance quality training has led to a great blindness in endurance quality training. The endurance quality level evaluation of young male basketball players is a classic multiple attribute group decision making (MAGDM) issue with vague, inconsistent, and indeterminate information. The 2-tuple linguistic neutrosophic sets (2TLNSs) is an appropriate form to express the indeterminate decision-making information in the endurance quality level evaluation of young male basketball players. Therefore, in this paper, the 2-tuple linguistic neutrosophic numbers CLVA (2TLNN-CLVA) is built based on traditional close value (CLVA) method and applies it to evaluate the endurance quality level of young male basketball players. Finally, a numerical example for evaluating the endurance quality level of young male basketball players has been given and some decision comparisons are also conducted to further illustrate the advantages of the 2TLNN-CLVA method.

Keywords: Multiple attribute group decision making (MAGDM) problems, 2-tuple linguistic neutrosophic sets (2TLNSs), CLVA method, endurance quality level, basketball players

DOI: 10.3233/JIFS-224327

Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 6, pp. 9003-9014, 2023