The fault diagnosis layer model of electric power grid based on weighted mean roughness
Ran Li, Jinghua Li · 2005
Based on rough set, this paper use discernibility matrix to reduce the condition attributes. The reduced samples are laid by weighted mean roughness to avoid blindness and redundancy. By this method, model space can be compressed greatly and weighted mean roughness is easy to calculate. Weighted mean roughness is used to separate attributes' priority in every lay, which make the diagnosis system had strong tolerant ability. When the electric power grid is fault, the result of diagnosis will be correct by searching every lay with priority level. The correctness and effectiveness are validated by the analysis result of emulation.