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| Soldering Parameter-Setting Approach Based on Improved Adaptive Neuro Fuzzy Inference Model |
| SHA Jian-Jun, PAN erShun |
| (School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240, China) |
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Abstract To solve the problem in setting parameters for nonlinear dynamic system, an adaptive neuro fuzzy inference system was adopted to model the dynamic I/O system. A neural network predictor was introduced to enhance the adaptive ability of fuzzy neural networks and nonlinear approximation ability. By virtue of the nearest neighbor clustering algorithm, the parameters and the structure of the fuzzy rules were adjusted and updated, which improves the accuracy of fuzzy reasoning and enhances the system’s fault tolerance and robustness. The simulation experiment’s result shows that the proposed method can effectively achieve the quick and accurate setting of the nonlinear I/O system parameters.
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Received: 25 October 2010
Published: 31 December 2011
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