Flatness Pattern Recognition Based on Adaptive Neuro-Fuzzy Inference System
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As the antijamming ability of the traditional least squares flatness pattern recognition method is poor,its precision is low,the result of the neural network flatness pattern recognition method has a long time network studying,being easy to fall into the local minimum and many other problems like these.The research fuses the merits of the fuzzy theories and neural network,fitting effectively three adaptive neuro-fuzzy inference system,and proposes a kind of flatness pattern recognition method based on adaptive neuro-fuzzy inference system.The findings indicate that this method can overcome the above flaw very well,and can distinguish the common flatness flaw effectively,the recognition speed and the precision can be improved to some degree,and the recognition result is also very close to the actual value of flatness control meter.