Comparison of various types of inverse soft covering upper approximations with an application to decision making

This study presents a comparison of various inverse soft covering upper approximations, focusing specifically on the differences between them. A key finding of our work is the introduction of a new type of inverse soft covering upper approximation which is a new approach in developing inverse soft covering based rough sets. We demonstrate that this new approximation is smaller than the three existing approximations described in the literature. Based on this result, we aim to manage the decision-making processes, especially for the uncertainty problems, in a more ideal way.