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The theory of cubic bipolar fuzzy sets (CBFSs) is a robust approach for dealing with vagueness and bipolarity in real-life circumstances. This theory provides a hybrid machine learning paradigm that can accurately describe two-sided contrasting features for medical diagnosis. The ELECTRE-II model, which is extensively used, is expanded in this article to include the cubic bipolar fuzzy (CBF) context. In order to produce a comprehensive preference ordering of actions, ELECTREII establishes two different forms of embedded outranking relations while taking into account the subjective human judgments. A huge number of applications have been created by its variations under various models, considering the CBF model's greater capacity to deal. For opinions in the adaptive CBF structure with unknown information, the CBF-ELECTRE-II group decision support method is described. With the use of proper CBF aggregation operations, the expert CBF views on each alternative and criterion are compiled in the first step. The approach then constructs weak and strong outranking relations and offers three distinct CBF outranking set kinds ("concordance", "indifferent" and "discordance" sets). Strong and weak outranking graphs serve as a visual depiction of the latter, which is finally studied by a rigorous iterative procedure that yields a preferred system. For these objectives, integrated CBF-VIKOR and CBF-ELECTRE-II techniques are developed for multi-criteria group decision making (MCDGM). Finally, suggested techniques are recommended to determine ranking index of efficient road freight transportation (FRT) in Industry 4.0. The ranking index and optimal decision are also computed with other techniques to demonstrate robustness of proposed MCDGM approach. [ABSTRACT FROM AUTHOR]

In the present work, we bring out some properties of bipolar fuzzy soft topology (BFS-topology) by using the concept of Q-neighborhood. Firstly, we define the concept of quasi-coincident and Q-neighborhood for BFS-point and BFS-set, then we discuss certain properties of BFS topology including, BFS-accumulation point, BFS-dense subset, BFS countability axioms and BFS-separable space by utilizing BFS Q-neighborhood. We also study the concept of BFS-Lindelöf space. Furthermore, we apply the concept of BFS quasi-coincident in decision-making of a real world problem by using BFS-AND, BFS-OR operations. [ABSTRACT FROM AUTHOR]