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The Application of BP Neural Network Based on Improved Adaptive Genetic Algorithm in Bridge Construction Control

机译:改进自适应遗传算法的BP神经网络在桥梁施工控制中的应用。

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Convergence and local optimization is the main limitation of traditional BP Neural network. In order to overcome these problems, an improved adaptive genetic algorithm is proposed to optimize the Bp neural network's parameters in this paper. Network's convergence time will be reduced by using new algorithm , which has better stability than traditional one. The results show that this new algorithm is effective to forecast the deflection during the bridge construction control.
机译:收敛和局部优化是传统BP神经网络的主要局限性。为了克服这些问题,本文提出了一种改进的自适应遗传算法来优化Bp神经网络的参数。通过使用新算法可以减少网络的收敛时间,该算法比传统算法具有更好的稳定性。结果表明,该新算法可有效预测桥梁施工控制过程中的挠度。

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