The article presents a new method to reduce attributes in rough set theory, which helps analyze messy and incomplete data. The researchers developed an improved algorithm that determines the importance of attributes using information entropy. By focusing on the most significant attributes, they created a more effective decision-making process for large datasets. The algorithm was tested on digital images and proved to be successful in determining flame stability.