A neuro-fuzzy approach to gear system monitoring
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Neural Networks
Application Research of Support Vector Machines in Dynamical System State Forecasting
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Reliable prediction system based on support vector regression with genetic algorithms
ICNC'09 Proceedings of the 5th international conference on Natural computation
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In this paper, an adaptive neuro-fuzzy (NF) forecasting system is proposed, and its robustness is investigated experimentally. After the NF predictor is initially trained using a data set from the Mackey-Glass differential equation, it is implemented for two applications, an online gear system condition monitoring and a material fatigue testing to forecast future states of a fatigue crack propagation trend in test specimens. From the forecasting tests and simulation analyses, it is found that the developed NF system is a very reliable prognostic scheme; it can capture system dynamic behavior quickly, and track system responses accurately.