BLASTING, Volume. 40, Issue 3, 199(2023)

Establishment and Application of Blasting Vibration Prediction System based on SSA-XGBoost

ZOU Ping1... WANG Liang2, DAI Yong1 and ZHANG Chun-yang3 |Show fewer author(s)
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  • 1[in Chinese]
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  • 3[in Chinese]
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    References(15)

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    [3] [3] DAI Y,KHANDELWAL M,QIU Y,et al.A hybrid metaheuristic approach using random forest and particle swarm optimization to study and evaluate backbreak in open-pit blasting[J].Neural Computing and Applications,2022: 1-16.

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    [10] [10] KHANDELWAL M,ARMAGHANI D J,FARADONBEH R S,et al.Classification and regression tree technique in estimating peak particle velocity caused by blasting[J].Engineering with Computers,2017,33: 45-53.

    [12] [12] ARMAGHANI D J,HASANIPANAH M,AMNIEH H B,et al.Feasibility of ICA in approximating ground vibration resulting from mine blasting[J].Neural Computing and Applications,2018,29: 457-465.

    [14] [14] FAN Yong,PEI Yong,YANG Guang-dong,et al.Prediction of blasting vibration velocity peak based on an improved PSO-BP neural network[J].Journal of Vibration and Shock,2022,41(16): 194-203, 302.DOI: 10.13465/j.cnki.jvs.2022.16.025.(in Chinese)

    [16] [16] GUO Qin-peng,YANG Shi-jiao,ZHU Zhong-hua,et al.Prediction of blasting vibration velocity using GA-BP neural network[J].Blasting,2020,37(3): 148-152.(in Chinese)

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    ZOU Ping, WANG Liang, DAI Yong, ZHANG Chun-yang. Establishment and Application of Blasting Vibration Prediction System based on SSA-XGBoost[J]. BLASTING, 2023, 40(3): 199

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    Paper Information

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    Received: Apr. 18, 2023

    Accepted: --

    Published Online: Jan. 15, 2024

    The Author Email:

    DOI:10.3963/j.issn.1001-487x.2023.03.027

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