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The Application of the Improved RBF in the Semiconductor Manufacturing System Feeding Control

机译:改进的RBF在半导体制造系统馈送控制中的应用

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According to the complexity of the semiconductor manufacturing processes, a RBF neural network improved by GA is put forward to apply in the semiconductor production modeling and predict the line performance indexes. The improved RBF algorithm can play better role in dealing with the dynamic real-time data from the line, building predictive models to describe line dynamic behavior, and presenting future outputs based on the current inputs accurately. In this paper, the improved RBF algorithm and the traditional RBF neural network are performed respectively to realize the line modeling simulation. Finally, the simulation result shows the effectiveness of this improved algorithm.
机译:根据半导体制造工艺的复杂性,通过GA改善的RBF神经网络被提出在半导体生产建模中应用并预测线路性能指标。改进的RBF算法可以在处理来自线路的动态实时数据时发挥更好的作用,构建预测模型来描述线动态行为,并准确地呈现当前输入的未来输出。本文分别执行改进的RBF算法和传统的RBF神经网络,以实现线路建模仿真。最后,仿真结果显示了这种改进算法的有效性。

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