| 期刊全稱 | Applications of Artificial Intelligence in Tunnelling and Underground Space Technology | | 影響因子2023 | Danial Jahed Armaghani,Aydin Azizi | | 視頻video | http://file.papertrans.cn/160/159303/159303.mp4 | | 發(fā)行地址 | Presents statistical and intelligent computational techniques to calculate the performance of tunnel boring machine (TBM).Includes a review of available TBM performance predictive models in detail.Int | | 學(xué)科分類 | SpringerBriefs in Applied Sciences and Technology | | 圖書(shū)封面 |  | | 影響因子 | .This book covers the tunnel boring machine (TBM) performance classifications, empirical models, statistical and intelligent-based techniques which have been applied and introduced by the researchers in this field. In addition, a critical review of the available TBM performance predictive models will be discussed in details. Then, this book introduces several predictive models i.e., statistical and intelligent techniques which are applicable, powerful and easy to implement, in estimating TBM performance parameters. The introduced models are accurate enough and they can be used for prediction of TBM performance in practice before designing TBMs. ??. | | Pindex | Book 2021 |
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