caa a22 4500 605454086 CHVBK 20210128100205.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s10064-014-0657-x doi (NATIONALLICENCE)springer-10.1007/s10064-014-0657-x Ground vibration prediction in quarry blasting through an artificial neural network optimized by imperialist competitive algorithm [Elektronische Daten] [Mohsen Hajihassani, Danial Jahed Armaghani, Aminaton Marto, Edy Tonnizam Mohamad] Vibrations au sol prédiction dans quarry dynamitage à travers un réseau neural artificiel optimisé par une concurrence impérialiste algorithme This paper presents a new hybrid artificial neural network (ANN) optimized by imperialist competitive algorithm (ICA) to predict peak particle velocity (PPV) resulting from quarry blasting. For this purpose, 95 blasting works were precisely monitored in a granite quarry site in Malaysia and PPV values were accurately recorded in each operation. Furthermore, the most influential parameters on PPV were measured and used to train the ICA-ANN model. Considering the measured data from the granite quarry site, a new empirical equation was developed to predict PPV. For comparison, a pre-developed ANN model was developed for PPV prediction. The results demonstrated that the proposed ICA-ANN model is able to predict blasting-induced PPV better than other presented techniques. Springer-Verlag Berlin Heidelberg, 2014 Blast safety area nationallicence Ground vibration nationallicence Peak particle velocity nationallicence Artificial neural network nationallicence Imperialist competitive algorithm nationallicence Blast zone de sécurité au sol nationallicence vibrations, Pic de vélocité à particules nationallicence réseaux de neurones artificiels nationallicence concurrentielle impérialiste algorithme nationallicence Hajihassani Mohsen Construction Research Alliance, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut Jahed Armaghani Danial Faculty of Civil Engineering, Department of Geotechnics and Transportation, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut Marto Aminaton Faculty of Civil Engineering, Department of Geotechnics and Transportation, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut Tonnizam Mohamad Edy Faculty of Civil Engineering, Department of Geotechnics and Transportation, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut Bulletin of Engineering Geology and the Environment Springer Berlin Heidelberg 74/3(2015-08-01), 873-886 1435-9529 74:3<873 2015 74 10064 https://doi.org/10.1007/s10064-014-0657-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10064-014-0657-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hajihassani Mohsen Construction Research Alliance, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut NATIONALLICENCE 700 1- Jahed Armaghani Danial Faculty of Civil Engineering, Department of Geotechnics and Transportation, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut NATIONALLICENCE 700 1- Marto Aminaton Faculty of Civil Engineering, Department of Geotechnics and Transportation, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut NATIONALLICENCE 700 1- Tonnizam Mohamad Edy Faculty of Civil Engineering, Department of Geotechnics and Transportation, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor, Malaysia aut NATIONALLICENCE 773 0- Bulletin of Engineering Geology and the Environment Springer Berlin Heidelberg 74/3(2015-08-01), 873-886 1435-9529 74:3<873 2015 74 10064