Virtual Learning Analysis Using Complex Rule-Based Approach in the Context of Cloud Computing

Customers interactive experience make distance learning more accessible through Virtual Reality Learning (VRL).The functioning of an application can be disrupted and cyber-illness result the inability to maintain high performance and secure data transmission in critical areas of the VRL system. In this study, we introduce a new rule-based <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$3 Q S$</tex> modification system to manage cyber-illness caused by performance/security abnormalities during VRL sessions. This approach provides a risk and expenditure-based compromise analysis. Framework's integration to a social VRL keeps track of performance and safety anomalies of connection and session information. A system includes rule-based adjustments, which are triggered using different decision criteria during the learning. Based on the results of the experiments, the researchers show that the rule based 3QS adaptive system efficiently reduces cyber illness levels while preserving application software. The proposed system implemented the appropriate approaches to address performance and security challenges to create a strong and reliable social VRL.