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Applications of Artificial Intelligence in Tunnelling and Underground Space Technology / / by Danial Jahed Armaghani, Aydin Azizi



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Autore: Armaghani Danial Jahed Visualizza persona
Titolo: Applications of Artificial Intelligence in Tunnelling and Underground Space Technology / / by Danial Jahed Armaghani, Aydin Azizi Visualizza cluster
Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
Edizione: 1st ed. 2021.
Descrizione fisica: 1 online resource (IX, 70 p. 16 illus., 15 illus. in color.)
Disciplina: 622.028
Soggetto topico: Engineering geology
Statistical Physics
Geotechnical engineering
Mathematical statistics
Manufactures
Engineering mathematics
Geoengineering
Geotechnical Engineering and Applied Earth Sciences
Mathematical Statistics
Machines, Tools, Processes
Engineering Mathematics
Persona (resp. second.): AziziAydin
Nota di contenuto: 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.
Sommario/riassunto: 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. .
Titolo autorizzato: Applications of artificial intelligence in tunnelling and underground space technology  Visualizza cluster
ISBN: 981-16-1034-7
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910483423303321
Lo trovi qui: Univ. Federico II
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Serie: SpringerBriefs in Applied Sciences and Technology, . 2191-5318