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This paper is based on the background of the development of aviation fault diagnosis expert system. To solve the engineering problems of the low interpretation efficiency encountered in the construction of expert system, a reasoning machine based on the combination of Fault Tree (FT) and Generalized Regression Neural Network (GRNN) is brought forward. First, the FT model is built and simplified. Second,...
At present, aircraft fault diagnosis methods have been used in many engineering applications. Among them, most methods considered only a single case-based or rule-based diagnostic method, therefore the efficiency of those fault diagnosis methods need to be improved. In this paper, it proposed and studied a fault diagnosis method based on the integration of case and rule reasoning, and introduced the...
Data mining based on rough set is introduced into CBR (Case-based Reasoning) system. And learning model of case base is established. The potential knowledge of case base is obtained and studied, through attribute reduction and attribute value reduction. Meanwhile, the structure and performance of case base is maintained and improved, through case reduction. The establishment of case base learning...
For target tracking in Interference Environments of cognitive radar problem, Extended Karman, Particle filter algorithms etc. are generally used to be regarded as usual solutions to state estimation. Many techniques have been developed to improve performance of target tracking. In this paper, we set the structure and key features of target's tracking design for cognitive radar, and newly propose cognitive...
This paper describes the development of an expert planning framework for design of control systems. The expert planner incorporates the knowledge of a control system designer in selecting and applying mathematical algorithms from several branches of control theory such as Kalman filter design, proportional/integral/ derivative control, and optimal state feedback. The framework has been developed directly...
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