Abstract: Because of the lack of efficiency evaluation method，the knowledge-sharing efficiency evaluation model based on rough sets and RBF neural network（Rough Set and Radial Basis Function Neural Network，R-RNN） is proposed in this paper.Firstly，the process of knowledge-sharing is researched，the efficiency affecting factors of knowledge-sharing is analyzed，and then the index system of efficiency evaluation is constructed.Secondly，the theory of rough set is utilized to rationalize the knowledge-sharing efficiency evaluation index system and reduce the input dimensionality of RBF neural network.Then，RBF neural network is used to get the synthetic evaluation value of knowledge-sharing efficiency.Finally，an application example is given to validate the feasibility and effectiveness of the model.

Key words: knowledge sharing, efficiency evaluation, index system, rough set, Radial Basis Function（RBF） neural network

摘要： 针对企业知识共享效率评价方法缺乏的现状，提出了基于粗糙集和RBF神经网络的R-RNN知识共享效率评价模型。在研究知识共享活动基本过程的基础上，分析了知识共享效率影响因素，得出效率评价指标体系。然后，运用粗糙集理论对评价指标进行预处理，去除冗余指标项，在合理化评价指标体系的同时减少网络输入维度，进而采用RBF神经网络对知识共享效率进行综合评价。最后通过具体的应用实例验证了该评价模型的有效性与可行性。

关键词: 知识共享, 效率评价, 指标体系, 粗糙集, RBF神经网络