This study intends to significantly enhance the capacity of decision experts (DEs) to capture
their judgment in a larger area. In order to accomplish this, we propound the-spherical fuzzy …

The, q-quasirung orthopair fuzzy set (,-ROFS) is a potent tool for representing fuzziness and
uncertainty compared to the-rung orthopair fuzzy set (-ROFS). This research aims to …

Complex fuzzy (CF) sets (CFSs) play an important role in modeling two-dimensional
information challenges. Researchers exploring decision-making systems have recently …

Machine learning (ML) is one of the dominating technologies practiced in both the industrial
and academic domains throughout the world. ML algorithms can examine the threats and …

Cyber-attacks are getting increasingly complex, and as a result, the functional concerns of
intrusion-detection systems (IDSs) are becoming increasingly difficult to resolve. The …

Deep neural networks (DNN) are highly effective in a number of tasks related to machine
learning across different domains. It is quite challenging to apply the information gained to …

The paper aims are to impersonate some robust sine-hyperbolic operations laws to
determine the group decision-making process under the fractional orthotriple linear …

The core objective of this security research is to ensure that healthcare software (HS) is
secure when operating on a fully functional quantum computer. Developers are constantly …

DDoS attack effect evaluation is the basis of security strategy deployment. The traditional
effect evaluation method relies on the original data, ignoring the relationship between …

The persistent evolution of cyber threats has given rise to Gen V Multi-Vector Attacks,
complex and sophisticated strategies that challenge traditional security measures. This …