Abstract:

Traditional variable precision multi-granulation rough sets are based on a single threshold while the multi-granulation rough set model processes data from multiple perspectives and multi-level. Data acquisition methods of different knowledge granularity are not the same and the noise data is also different. So the variable precision thresholds of different knowledge granularity levels should be different, which makes the traditional model incapable of adapting to the multi-granulation environment. In order to solve this problem, we propose a variable precision multi-granulation rough set model based on multiple thresholds. The model makes the variable precision threshold of different levels of knowledge granularity can be adjusted independently and it is more consistent with the data features of the multi-granulation rough set model. The model combines the multi-granulation rough set model and the variable precision rough set model with a more suitable method，which can solve the problem from multiple perspectives and has more flexible fault tolerance ability.

Key words: multi-granulation rough set model, variable precision rough set model, multiple thresholds, knowledge granularity