中图分类号： TN914；TP391 文献标识码： A DOI：10.16157/j.issn.0258-7998.201012 中文引用格式： 刘俊卿，刘进，肖龙忠. 一种基于灰色RBF神经网络的系统效能评估方法[J].电子技术应用，2020，46(12)：107-110. 英文引用格式： Liu Junqing，Liu Jin，Xiao Longzhong. A method of system effectiveness evaluation based on grey RBF neural network[J]. Application of Electronic Technique，2020，46(12)：107-110.
A method of system effectiveness evaluation based on grey RBF neural network
Liu Junqing，Liu Jin，Xiao Longzhong
Wuhan Institute of Ship Communication，Wuhan 430205，China
Abstract： In order to solve the problem of comprehensive effectiveness evaluation of the system with complex composition, diverse functions and poor samples, this paper constructs a system effectiveness evaluation model based on grey theory, RBF neural network and grey RBF neural network according to the three-tier structure of the system effectiveness evaluation index system. The simulation results show that the accuracy of the grey RBF neural network model is higher than that of the grey model and RBF neural network. Through the grey RBF neural network model, we can accurately evaluate the comprehensive effectiveness of the system with various functions, complex composition, few samples.
Key words : index system；efficiency evaluation；grey theory；RBF neural network；grey RBF neural network