Group decision-making based on 2-tuple linguistic T-spherical fuzzy COPRAS method

Data mining is a thoroughly advanced method that evaluates and makes more sense of a variety in electronic commerce (e-commerce)-related knowledge, discovering useful ideas, predicting user actions, and assisting enterprises selection in modifying competitive strategy, minimizing cost, and attaining the finest results. Data mining has already become more popular in recent years. In this research paper, we propose a multi-attribute group decision-making (MAGDM) method under T-spherical fuzzy environment for selecting an optimal data mining strategy which is an important part of modern decision-making research. The information aggregation operators play an important role in solving MAGDM problems. Some point aggregation operators based on the 2-tuple linguistic T-spherical fuzzy numbers, including 2-tuple linguistic T-spherical fuzzy point weighted averaging (2TLT-SFPWA) operator, 2-tuple linguistic T-spherical fuzzy point weighted geometric (2TLT-SFPWG) operator, 2-tuple linguistic T-spherical fuzzy generalized point weighted averaging (2TLT-SFGPWA) operator and 2-tuple linguistic T-spherical fuzzy generalized point weighted geometric (2TLT-SFGPWG) operator, are proposed which competently capture all the aspects of human opinions expressible in terms of yes, no, cessation and denial with no limitation. The proposed aggregation operators are valid and have some basic properties which are keenly analyzed. Furthermore, the complex proportional assessment (COPRAS) method is developed on the basis of 2-tuple linguistic T-spherical fuzzy point aggregation operators. Finally, a numerical example is illustrated for demonstrating the effectiveness of the proposed work along with comparative analysis which verifies the reliability and efficacy of its outcomes. In the end, we conclude some results from the numerical analysis, i.e., to balance the long-term development of e-commerce, data mining can mine massive amounts of data which boosts the growth of e-commerce in future.