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GA-NN Monitoring Model and its Application on Surface Settlement

机译:GA-NN监测模型及其在表面沉降中的应用

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Combining the advantages of basic genetic algorithm and neural network, analyze and set up GA & NN genetic neural network, explore and study the algorithm. The efficiency and effectiveness of this hybrid training has been significantly improved comparing with the single genetic evolution or BP training method, its versatility is better. The model is applied to predict the deformation of shield tunnel excavation. According to the effects of measured influence factors under construction, it can make the appropriate forecast to the surface settlement which is better than the conventional regression model. It shows that neural networks in the ground during tunneling shield analysis and prediction of settlement is practical and adaptable.
机译:结合基本遗传算法和神经网络的优势,分析和设置GA&NN遗传神经网络,探索和研究算法。与单一遗传演进或BP训练方法相比,这种混合培训的效率和有效性得到了显着改善,其多功能性更好。该模型应用于预测屏蔽隧道挖掘的变形。根据测量的影响因素的施工影响,它可以对表面沉降的适当预测优于传统回归模型。它表明,在隧道屏蔽分析期间,地面的神经网络是实用的和适应性的。

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