In this paper, proposed a model of BP neural network based on improved DNA genetic algorithm, applied it to monitor and forecast cutting tool wear. Designed subsection crossover and subsection mutation based on process code, adopted fitness scaling method and ranking method to select
operators, optimized the initial weight values of BP neural network, repeatedly trained the BP neural network model, improved the overall convergence rate, avoided falling into local minimum, improved the precision and accuracy of prediction. Through simulation, tested the designed method
performance, compared with other test results, the simulation results show the effectiveness of the proposed method.
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