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Logistics demand forecasting is an important process between Logistics programming and Logistics resource allocation. The neural network algorithm is usually applied to forecasting logistics demand. However it has the problems of slow convergence and local optimization in searching results when the training data is excessive. This paper presents an adaptive(More)
  • Bu Xuhui
  • 2009 International Asia Symposium on Intelligent…
  • 2009
The iterative learning control is applied to electromagnetic vibrating machine in blending system, which executes the same task repeatedly over a finite time-interval. The iterative learning controller of electromagnetic vibrating machine amplitude is provided and the convergence analysis is also given. This technique uses the operation information in(More)
Taking into account internal and exterior factors of rockburst, a model using BP neural network is proposed, in which the in-situ stress, the compressive strength, the tensile strength and the elastic energy index of the cavern are chosen as criteria indexes. Some representative engineering projects at home and aboard are collected as learning and training(More)
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