Neurofuzzy Modelling
暂无分享,去创建一个
A neural network can approximate a function, but it is impossible to interpret the result in terms of natural language. The fusion of neural networks and fuzzy logic in neurofuzzy models provide learning as well as readability. Control engineers find this useful, because the models can be interpreted and supplemented by process operators.
[1] James M. Keller,et al. Incorporating Fuzzy Membership Functions into the Perceptron Algorithm , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Michio Sugeno,et al. Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.
[3] Chuen-Tsai Sun,et al. Neuro-fuzzy modeling and control , 1995, Proc. IEEE.