Neutrosophic over soft generalized continuous functions: a paradigm shift in best invention competition machine selection

Abstract

In today’s complex and uncertain world, the emergence of neutrosophic environments is becoming increasingly essential. These frameworks excel at navigating ambiguity, providing valuable tools for understanding and managing uncertainty. A significant advancement in this field is the introduction of Neutrosophic Over Soft Generalized Closed Sets and Continuous Functions. These concepts offer refined methods for grappling with nuanced uncertainties, providing a deeper understanding of complex situations. To illustrate their effectiveness, let’s consider a practical example involving the selection of machines for the prestigious Best Invention Competition. By employing tangent similarity measures, we can identify optimal candidates with precision. This numerical demonstration vividly showcases the tangible utility of these concepts in decisionmaking within intricate and uncertain landscapes. Furthermore, this example hints at the transformative potential of neutrosophic frameworks across various domains. These concepts promise to enhance problem-solving capabilities in contexts where uncertainty is prevalent, enabling the emergence of more informed and resilient decisions.