Automated intelligent hybrid computing schemes to predict blasting induced ground vibration
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,General Engineering,Modeling and Simulation,Software
Link
https://link.springer.com/content/pdf/10.1007/s00366-021-01444-1.pdf
Reference56 articles.
1. Abbaszadeh Shahri A, Asheghi R (2018) Optimized developed artificial neural network based models to predict the blast-induced ground vibration. Innov Infrastruct Solut 3:34. https://doi.org/10.1007/s41062-018-0137-4
2. Sołtys A, Twardosz M, Winzer J (2017) Control and documentation studies of the impact of blasting on buildings in the surroundings of open pit mines. J Sustain Min 16(4):179–188. https://doi.org/10.1016/j.jsm.2017.12.004
3. Tripathy GR, Shirke RR, Kudale MD (2016) Safety of engineered structures against blast vibrations: a case study. J Rock Mech Geotech Eng 8(2):248–255. https://doi.org/10.1016/j.jrmge.2015.10.007
4. Ak H, Iphar M, Yavuz M, Konuk A (2009) Evaluation of ground vibration effect of blasting operations in a magnesite mine. Soil Dyn Earthq Eng 29(4):669–676. https://doi.org/10.1016/j.soildyn.2008.07.003
5. Taheri K, Hasanipanah M, Bagheri Golzar S, Abd Majid MZ (2016) A hybrid artificial bee colony algorithm-artificial neural network for forecasting the blast-produced ground vibration. Eng Comput. https://doi.org/10.1007/s00366-016-0497-3
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