Extension of Interaction Aggregation Operators for the Analysis of Cryptocurrency Market Under q-Rung Orthopair Fuzzy Hypersoft Set

One of the substantial innovations achieved through digitalization is cryptocurrencies, also known as simulated or digital currencies, which have been deliberated in the modern era as a new platform particularly suitable for financiers. Several cryptocurrencies, such as Bitcoin, Ethereum, Binance Coin, and Tether, do not trust a dominant expert. The classification and conduction of insecurity and the confirmation of digital currencies complicate decision-making. q-rung orthopair fuzzy hypersoft sets are an emerging arena of research intended to report the confidential restrictions of q-rung orthopair fuzzy soft sets on multiparameter indefinite functions. Such a function maps a tuple of sub-parameters to a power set of the universe. It emphasizes allocating attributes to their corresponding sub-attribute values in disjoint sets. These structures sort it an innovative systematic tool for addressing the obstacles of hesitancy. The q-rung orthopair fuzzy hypersoft set (q-ROFHSS) expertly compacts with tentative and ambagious facts equated to the existing q- rung orthopair fuzzy soft set and Pythagorean fuzzy hypersoft set (PFHSS). It is the most compelling mode for enlarging imprecise data in decision-making (DM). This investigation’s ultimate impartiality is presenting interactional algebraic operational laws for q-ROFHSS. Furthermore, some interaction aggregation operators (AOs) have been anticipated via our proposed operational laws, such as q-rung orthopair fuzzy hypersoft interactive weighted average (q-ROFHSIWA) and q-rung orthopair fuzzy hypersoft interactive weighted geometric (q-ROFHSIWG) operators with their essential properties. In reality, a mathematical illustration of DM obstacles is pondered to substantiate the proven technique’s dominance. Based on the projected interaction AOs, robust multi-criteria group decision-making (MCGDM) design has been offered, which carries the most practical consequences associated with predominant MCGDM methods. The significance spectacle is that the intentional methodology is more operative and steady in bearing weird facts based on q-ROFHSS.