Multiple Source Knowledge Fusion Technique Based on Fuzzy Sets Theory

In the field of knowledge management, new knowledge level can be formed via multiple source knowledge fusion according to the characteristics of knowledge source, while the connotation, level and confidence of knowledge, as well as the ability to fulfill the system mission can be enhanced. The structure and framework of knowledge fusion is obtained from research on multiple source knowledge fusion at the foundation of the three fusion levels of basic knowledge level, method level and thought level. By introducing information fusion processing into knowledge fusion, a knowledge fusion algorithm based on fuzzy sets theory is formed. Besides, the processing flow and a fusion model based on Petri net are advanced. By utilizing the knowledge fusion algorithm based on fuzzy sets theory, the corporate failure prediction problem is discussed by synthesizing the observation results of different prediction models. It is proved by real examples and simulation results that the uncertainty of corporate failure prediction is reduced by knowledge fusion determination methods and the application of knowledge fusion in the field of knowledge management is effective and feasible.