A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network
Flyrock is one of the major disturbances induced by blasting which may cause severe damage to nearby structures. This phenomenon has to be precisely predicted and subsequently controlled through the changing in the blast design to minimize potential risk of blasting. The scope of this study is to pr...
Saved in:
| Main Authors: | Aminaton Marto, Mohsen Hajihassani, Danial Jahed Armaghani, Edy Tonnizam Mohamad, Ahmad Mahir Makhtar |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/643715 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Application of Artificial Neural Network for Predicting Shaft and Tip Resistances of Concrete Piles
by: Ehsan Momeni, et al.
Published: (2015-01-01) -
Application of UAVs to Support Blast Design for Flyrock Mitigation: A Case Study from a Basalt Quarry
by: Józef Pyra, et al.
Published: (2025-08-01) -
Application of imperialist competitive optimization algorithm in power industry
by: Mohammad Shahrazad, et al.
Published: (2015-01-01) -
Optimization of Hydrogen Distribution Network by Imperialist Competitive AlgorithmIn
by: M Omidifar, et al.
Published: (2016-07-01) -
Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis
by: Yulin Zhang, et al.
Published: (2025-05-01)