With the development of the Internet of Things (IoT), Hybrid Information Systems (HIS) collect increasing number of hybrid data. A novel Gaussian kernel Fuzzy Rough Sets (FRS) was constructed based on a new hybrid distance in our previous study. In real applications, with the deepening of cognition or improvement of technology, attribute values often change. There are three cases of changes: missing values are imputed, error values are corrected and values are coarsened or refined. In this paper, the mechanisms of attribute values changes and fuzzy e-quivalence relation in FRS are analyzed, and several incremental approaches for updating approximations are discussed.