In this paper, we give the concept of Globular T-Spherical Fuzzy (G-TSF) Sets
(G-TSFSs) as an innovative extension of T-Spherical Fuzzy Sets (TSFSs) and
Circular Spherical Fuzzy Sets (C-SFSs). G-TSFSs represent membership,
indeterminacy, and non-membership degrees using a globular/sphere bound that
can offer a more accurate portrayal of vague, ambiguous, and imprecise
information. By employing a structured representation of data points on a
sphere with a specific center and radius, this model enhances decision-making
processes by enabling a more comprehensive evaluation of objects within a
flexible region. Following the newly defined G-TSFSs, we establish some basic
set operations and introduce fundamental algebraic operations for G-TSF Values
(G-TSFVs). These operations expand the evaluative capabilities of
decision-makers, facilitating more sensitive decision-making processes in a
broader region. To quantify a similarity measure (SM) between GTSFVs, the SM is
defined based on the radius of G-TSFSs. Additionally, Hamming distance and
Euclidean distance are introduced for G-TSFSs. We also present theorems and
examples to elucidate computational mechanisms. Furthermore, we give the G-TSF
Weighted Average (G-TSFWA) and G-TSF Weighted Geometric (G-TSFWG) operators.
Leveraging our proposed SM, a Multi-Criteria Group Decision-Making (MCGDM)
scheme for G-TSFSs, named G-TSF MCGDM (G-TSFMCGDM), is developed to address
group decision-making problems. The applicability and effectiveness of the
proposed G-TSFMCGDM method are demonstrated by applying it to solve the
selection problem of the best venue for professional development training
sessions in a firm. The analysis results affirm the suitability and utility of
the proposed method for resolving MCGDM problems, establishing its
effectiveness in practical decision-making scenarios.

本文提出了球形模糊扁球体 (G-TSFSs) 的概念，它作为模糊信息的创新扩展，通过使用球形 / 球限界来表示成员关系、不确定性和非成员度，更准确地描绘了模糊、不明确和不精确的信息，为决策过程提供了更全面的评估对象的能力。通过引入基于 G-TSFSs 半径定义的相似度度量 (SM)、Hamming 距离和欧几里得距离，建立了一些基本集合运算和基本代数运算来扩展决策者的评估能力，在更广泛的区域内促进更敏感的决策过程。此外，还提出了 G-TSF 加权平均 (G-TSFWA) 和 G-TSF 加权几何 (G-TSFWG) 操作符。通过应用该方法解决一个公司中专业发展培训场所的选择问题，验证了所提出的方法在实际决策场景中解决多准则群决策问题的适用性和有效性。