標題: Titlebook: Applications of Artificial Intelligence in Tunnelling and Underground Space Technology; Danial Jahed Armaghani,Aydin Azizi Book 2021 The A [打印本頁] 作者: 五個 時間: 2025-3-21 19:10
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作者: exceed 時間: 2025-3-21 22:22
Empirical, Statistical, and Intelligent Techniques for TBM Performance Prediction,e projects, estimation of the TBM performance is?considered as a significant issue since it?can be an influential parameter related to the project?cost. Hence, many scholars tried to develop simple, applicable, and powerful methodologies for the prediction of TBM performance. The total developed met作者: 漂浮 時間: 2025-3-22 01:03 作者: arrhythmic 時間: 2025-3-22 04:40 作者: 態(tài)學 時間: 2025-3-22 08:54
Danial Jahed Armaghani,Aydin AziziPresents 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作者: Arthr- 時間: 2025-3-22 14:15
SpringerBriefs in Applied Sciences and Technologyhttp://image.papertrans.cn/a/image/159303.jpg作者: 發(fā)微光 時間: 2025-3-22 19:45 作者: –LOUS 時間: 2025-3-22 22:11 作者: 拋媚眼 時間: 2025-3-23 05:19 作者: SCORE 時間: 2025-3-23 07:27 作者: AMITY 時間: 2025-3-23 10:53
Empirische Polizeiforschung IIIe projects, estimation of the TBM performance is?considered as a significant issue since it?can be an influential parameter related to the project?cost. Hence, many scholars tried to develop simple, applicable, and powerful methodologies for the prediction of TBM performance. The total developed met作者: IOTA 時間: 2025-3-23 14:35 作者: 輕快帶來危險 時間: 2025-3-23 19:57
Das Modell der Preisabsatzfunktiondo this, after reviewing the available literature, the data collected from the tunnel site and doing laboratory investigations, five important parameters, i.e., rock mass rating, Brazilian tensile strength, weathering zone, cutter head thrust force, and revolution per minute, were set as model input作者: 惡意 時間: 2025-3-24 01:01 作者: 不可侵犯 時間: 2025-3-24 02:20
Book 2021ve 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, pow作者: Dungeon 時間: 2025-3-24 08:06 作者: Bravado 時間: 2025-3-24 13:47 作者: 口訣 時間: 2025-3-24 18:23 作者: Madrigal 時間: 2025-3-24 19:02
2191-530X of available TBM performance predictive models in detail.Int.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 r作者: AORTA 時間: 2025-3-25 02:07
Empirische Polizeiforschung IIIir accuracy level is only suitable (coefficient of determination ~0.6) in many cases. On the other hand, these techniques are not good if there are some outlier data samples in the database. The best model category for TBM performance prediction is related to machine learning (ML) and artificial int作者: CLASH 時間: 2025-3-25 03:36 作者: CARE 時間: 2025-3-25 09:44 作者: 征稅 時間: 2025-3-25 14:52 作者: CHOIR 時間: 2025-3-25 18:55
Developing Statistical Models for Solving Tunnel Boring Machine Performance Problem,erformance prediction compared to simple regression models. A coefficient of determination of about 0.6 confirmed a suitable and applicable accuracy level for the developed LMR and NLMR equations in estimating TBM PR/AR.作者: Immunization 時間: 2025-3-25 23:16 作者: 外面 時間: 2025-3-26 00:58
Applications of Artificial Intelligence in Tunnelling and Underground Space Technology作者: 顛簸下上 時間: 2025-3-26 04:20
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