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BP feed-forward network is the most widely applied neural network. There are a number of algorithms currently. The respective strengths and weaknesses of 8 kinds of BP algorithm provided by the neural network toolbox in MATLAB are studied in the paper in order to choose a more appropriate and faster algorithms under different conditions. Based on this, the measurement of vacuum level with the method of magnetron-discharge is taken as an example to carry on the simulation, the convergence steps of a variety of BP algorithm are compared in different situations, the fast convergence property of trainlm is confirmed, the conclusion is obtained that BP algorithm can forecast the vacuum level.
Zhao et al. (Mon,) studied this question.