Suitability assessment of different vector machine regression techniques for blast-induced ground vibration prediction in Ghana-Reference-Cited by-同舟云学术

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Suitability assessment of different vector machine regression techniques for blast-induced ground vibration prediction in Ghana

Published:2021-02-22 Issue: Volume: Page:
ISSN:2363-6203
Container-title:Modeling Earth Systems and Environment
language:en
Short-container-title:Model. Earth Syst. Environ.

Author:

Temeng Victor Amoako^ORCID,Arthur Clement Kweku^ORCID,Ziggah Yao Yevenyo^ORCID

Funder

Ghana National Petroleum Corporation Professorial Chair in Mining Engineering

Publisher

Springer Science and Business Media LLC

Subject

Computers in Earth Sciences,Statistics, Probability and Uncertainty,General Agricultural and Biological Sciences,General Environmental Science

Link

http://link.springer.com/content/pdf/10.1007/s40808-021-01129-0.pdf

Reference88 articles.

1. Abda Z, Chettih M, Zerouali B (2020) Assessment of neuro-fuzzy approach based different wavelet families for daily flow rates forecasting. Model Earth Syst Environ. https://doi.org/10.1007/s40808-020-00855-1

2. Abdollahi F, Hosseini S, Sabet M, Esmaeili-Faraj SH, Amiri F (2020) A novel study of the gas lift process using an integrated production/injection system using artificial neural network approach. Model Earth Syst Environ. https://doi.org/10.1007/s40808-020-00958-9

3. Álvarez-Vigil AE, González-Nicieza C, López Gayarre F, Álvarez- Fernández MI (2012) Predicting blasting propagation velocity and vibration frequency using artificial neural networks. Int J Rock Mech Min Sci 55:108–116

4. Amnieh BH, Mozdianfard MR, Siamaki A (2010) Predicting of blasting vibrations in sarcheshmeh copper mine by neural network. Saf Sci 38(3):319–325

5. Armaghani DJ, Hasanipanah M, Amnieh HB, Mohamad ET (2018) Feasibility of ICA in approximating ground vibration resulting from mine blasting. Neural Comput Appl 29(9):457–465

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1. Optimization of an Artificial Neural Network Using Four Novel Metaheuristic Algorithms for the Prediction of Rock Fragmentation in Mine Blasting;Journal of The Institution of Engineers (India): Series D;2024-06-21

2. A comprehensive survey on machine learning applications for drilling and blasting in surface mining;Machine Learning with Applications;2024-03

3. Application of artificial intelligence in predicting blast-induced ground vibration;Applications of Artificial Intelligence in Mining, Geotechnical and Geoengineering;2024

4. Characteristics and Energy Distribution of Blast-Induced Ground Vibration in Deep-Hole Blasting;Buildings;2023-03-29

5. Intelligent ground vibration prediction in surface mines using an efficient soft computing method based on field data;Frontiers in Public Health;2023-02-01

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