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Artificial intelligence in underground development: a study of TBM performance

机译:地下发展中的人工智能:TBM性能研究

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Modelling tunnel boring machine (TBM) performance is an important aspect in tunnel operations. The use of artificial intelligence techniques such as artificial neural networks has been recently introduced to this subject and the results from such applications prove their potential in making accurate prognosis. This paper presents a review of feed-forward artificial neural network (ANN) development and furthermore it illustrates their application by the use of two cases studies from Italian and Greek underground projects, where the TBM performance is modelled. The results obtained show that the developed ANNs can efficiently generalise the TBM behaviour in their respective geotechnical environment, having a reliable, effective and consistent performance.
机译:建模隧道镗床(TBM)性能是隧道运营中的一个重要方面。最近将使用人工智能技术,例如人工神经网络,并将这些应用的结果引入了这种应用的结果证明了它们对准确预后的潜力。本文介绍了对前馈人工神经网络(ANN)开发的综述,此外,它通过使用来自意大利和希腊地下项目的两种案例研究来说明他们的应用,其中TBM性能是建模的。获得的结果表明,发达的ANN可以有效地概括其各自的岩土环境中的TBM行为,具有可靠,有效和一致的性能。

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