基于回歸神經網絡的復雜工業對象的建模

Modeling for A Complicated Industrial Object Based on Recurrent Neural Network

摘要: 討論一種動態神經網絡——Elman回歸神經網絡的結構和算法.基于這一網絡結構提出了非線性時變工業對象——直流電弧的神經網絡建模方法,并與用其他方法為對象建立的模型進行了比較,結果證明回歸網絡模型能夠很好地適配該工業對象,顯示了動態神經網絡在工業對象建模中的良好應用前景.

Abstract: The architecture and algorithm of a kind of dynamical neural network, Elman recurrent neural network (RNN)were dicussed. Based on this network, an approach of modeling for nonlinear time-varying industrial object, direct current arc, was proposed. Compared with other modeling method for the object, the model based on RNN is proved to have better performance.