Research On Knowledge Fusion Model Served For Innovation Performance Evaluation Of Manufacturing Enterprise

Since1995, as an independent field of study, knowledge fusion has been greatlydeveloped. Although in terms of basic theory construction is not perfect, but itsperformance in application fully embodies the value of knowledge fusion. In manyareas, knowledge fusion has proved able to help users solve the problem better.Therefore, knowledge fusion is used in evaluating enterprise innovation performance.Enable enterprises to understand the status of the current innovation better, and raisetheir innovation performance.This research uses rough sets theory and knowledge fusion to study the innovationperformance influencial factors of manufacturing enterprise. By studying innovationperformance factors related literature, combined with the availability of data, selectedthe innovation performance evaluation index. Reference to the preliminary ideas thatuse of rough set theory to bulid multi-knowledge bases, using fuzzy C-means clusteringalgorithm to complete the discretization of continuous attributes, reducted theinnovation performance evaluation index of manufacturing enterprise by geneticalgorithm,and construct several groups of enterprise innovation performance evaluationmodel by introduced attribute dependency and attribute importance of rough set theory.Then combine the evaluation model and the rule base formed by correspondingreduction to form a source of knowledge for knowledge fusion. Then, using the methodof fuzzy integral to integrate the output of multiple innovatioin performance evaluationmodels. And established the optimal decision fusion model which including the requestprocessing module, information collection module, multiple knowledge source buildingmodule, knowledge fusion module and the result feedback module. Completed therelated research on knowledge fusion model served for innovation performanceevaluation of manufacturing enterprise.Finally, select the159manufacturing companies listed in the SME as samples, andconduct applied research about optimal decision knowledge fusion model. Researchresults show that the evaluation results after knowledge fusion can more accuratelyjudge the innovation performance of the enterprise. Also found that the firms size andknowledge accumulation have the greatest effect on innovation performance. Firm sizehas a positive role in promoting innovation performance, while the knowledgeaccumulation and innovation performance has negative correlation.