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Applications of artificial intellige...

Armaghani, Danial Jahe.

Applications of artificial intelligence in tunnelling and underground space technology

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applications of artificial intelligence in tunnelling and underground space technologyby Danial Jahed Armaghani, Aydin Azizi.
Author:	Armaghani, Danial Jahe.
other author:	Azizi, Aydin.
Published:	Singapore :Springer Singapore :2021.
Description:	ix, 70 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	TunnelingEquipment and supplies.
Online resource:	https://doi.org/10.1007/978-981-16-1034-9
ISBN:	9789811610349$q(electronic bk.)

Applications of artificial intelligence in tunnelling and underground space technology
Armaghani, Danial Jahe.

Applications of artificial intelligence in tunnelling and underground space technology[electronic resource] /by Danial Jahed Armaghani, Aydin Azizi. - Singapore :Springer Singapore :2021. - ix, 70 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..

Chapter 1. An Overview of Field Classifications to Evaluate Tunnel Boring Machine Performance -- Chapter 2. Empirical, Statistical and Intelligent Techniques for TBM Performance Prediction. Chapter 3. Developing Statistical Models for Solving Tunnel Boring Machine Performance Problem -- Chapter 4. A Comparative Study of Artificial Intelligence Techniques to Estimate TBM Performance in Various Weathering Zones.

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.

ISBN: 9789811610349$q(electronic bk.)

Standard No.: 10.1007/978-981-16-1034-9doiSubjects--Topical Terms:

317162
Tunneling
--Equipment and supplies.

LC Class. No.: TA815 / .A763 2021

Dewey Class. No.: 624.193

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505 0 $a Chapter 1. An Overview of Field Classifications to Evaluate Tunnel Boring Machine Performance -- Chapter 2. Empirical, Statistical and Intelligent Techniques for TBM Performance Prediction. Chapter 3. Developing Statistical Models for Solving Tunnel Boring Machine Performance Problem -- Chapter 4. A Comparative Study of Artificial Intelligence Techniques to Estimate TBM Performance in Various Weathering Zones.
520 $a 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.
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