Aiming at the time-varying and nonlinear working characteristics of flue gas units, a BP neural network model based on genetic algorithm is proposed, and the time factor is added to the fitness function of the algorithm. The experimental results show that the genetic neural network considering the time algorithm is significantly better than the general BP neural network, its training time is greatly shortened, and the real-time performance of network calculation is enhanced.
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