top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Advances in Computational Intelligence in Geotechnical and Geological Engineering
Advances in Computational Intelligence in Geotechnical and Geological Engineering
Autore Armaghani Danial Jahed
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2024
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910978367803321
Armaghani Danial Jahed  
MDPI - Multidisciplinary Digital Publishing Institute, 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Applications of Artificial Intelligence in Tunnelling and Underground Space Technology / / by Danial Jahed Armaghani, Aydin Azizi
Applications of Artificial Intelligence in Tunnelling and Underground Space Technology / / by Danial Jahed Armaghani, Aydin Azizi
Autore Armaghani Danial Jahed
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
Descrizione fisica 1 online resource (IX, 70 p. 16 illus., 15 illus. in color.)
Disciplina 622.028
Collana SpringerBriefs in Applied Sciences and Technology
Soggetto topico Engineering geology
Statistical physics
Geotechnical engineering
Mathematical statistics
Manufactures
Engineering mathematics
Geoengineering
Statistical Physics
Geotechnical Engineering and Applied Earth Sciences
Mathematical Statistics
Machines, Tools, Processes
Engineering Mathematics
ISBN 981-16-1034-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNINA-9910483423303321
Armaghani Danial Jahed  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui