通过仿真研究验证了该方法能明显地改善常规模糊控制和固定预测步长的灰色预测模糊控制效果。

Simulation results show the superiority of the proposed method over the conventional fuzzy controller and the grey model predictive fuzzy controller with fix predictive step size.

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采用自适应变步长的后向传播算法（ABPM）构建了一个人工神经网络用水量预测模型。

The following paper constructs a artificial neural network - named water quantity predicting model, using automatically adapting and step-self-changing back propagation method(ABPM).

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结果显示，把最小二乘支持向量机回归预测与等步长时序预测相结合的预测方法应用于地下工程围岩位移监测数据的分析及预测是可行的；

Combining the advantages of regression analysis methods and time series forecast model with equal step length, a compound forecasting model was set up , and was tested with engineering data.

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