Fuzzy Synthetic Evaluation Model Based on the Knowledge System

Fuzzy measure, as a non-additive metric, is an effective tool for information fusion. Constructing a determining mechanism for fuzzy measure with operability is the key focus in academic and application fields. In this paper, we first take core samples as knowledge carriers on the decision information system. According to changes of knowledge carriers, we second give a knowledge-based metric of attributes importance. Third, combining with Choquet fuzzy integral, we establish a fuzzy synthetic evaluation model (denoted as BIS-FSEM) to deal with correlation indexes. And finally, we analyze the effectiveness of BIS-FSEM and give its implementation steps through a teaching quality evaluation case. Theoretical analysis and computation results show that BIS-FSEM has good operability and interpretability. It enriches the existing data-based metric theories of attributes importance to some extent. So it can be applied in many fields such as information fusion, synthetic evaluation and fuzzy decision-making.