This book gives a rigorous and up-to-date study of the various AI and machine learning algorithms for resolving environmental challenges associated with blasting. Blasting is a critical activity in any mining or civil engineering project for breaking down hard rock masses. A small amount of explosive energy is only used during blasting to fracture rock in order to achieve the appropriate fragmentation, throw, and development of muck pile. The surplus energy is transformed into unfavourable environmental effects such as back-break, flyrock, air overpressure, and ground vibration. The advancement of artificial intelligence and machine learning techniques has increased the accuracy of predicting these environmental impacts of blasting. This book discusses the effective application of these strategies in forecasting, mitigating, and regulating the aforementioned blasting environmental hazards.
| Autorius: | Ramesh M. Bhatawdekar, Aydin Azizi, Danial Jahed Armaghani, |
| Serija: | SpringerBriefs in Applied Sciences and Technology |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2022 |
| Knygos puslapių skaičius: | 88 |
| ISBN-10: | 9811682364 |
| ISBN-13: | 9789811682360 |
| Formatas: | Knyga minkštu viršeliu |
| Kalba: | Anglų |
| Žanras: | Geophysics |
Parašykite atsiliepimą apie „Environmental Issues of Blasting: Applications of Artificial Intelligence Techniques“
