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Study on Height Prediction of Water Flowing Fractured Zone in Deep Mines Based on Weka Platform

Author

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  • Liyang Bai

    (Department of Mining Engineering, Lyuliang University, Lvliang 033001, China
    State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan 232001, China
    State Key Laboratory Cultivation Base for Gas Geology and Gas Control, Henan Polytechnic University, Jiaozuo 454003, China
    Lvliang Engineering Research Center of Intelligent Coal Mine, Lvliang 033001, China)

  • Changlong Liao

    (State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan 232001, China)

  • Changxiang Wang

    (State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan 232001, China)

  • Meng Zhang

    (State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan 232001, China)

  • Fanbao Meng

    (School of Mechanicas Engineering, Shandong University of Science and Technology, Qingdao 266590, China)

  • Mingjin Fan

    (School of Mechanicas Engineering, Shandong University of Science and Technology, Qingdao 266590, China)

  • Baoliang Zhang

    (School of Architecture & Civil Engineering, Liaocheng University, Liaocheng 252000, China)

Abstract

Accurately predicting the height of water flowing fractured zone is of great significance to coal mine safety mining. In recent years, most mines in China have entered deep mining. Aiming at the problem that it is difficult to accurately predict the height of water flowing fractured zone under the condition of large mining depth, the mining depth, height mining, inclined length of working face and coefficient of hard rock lithology ratio are selected as the main influencing factors of the height of water flowing fractured zone. The relationship between various factors and the height of water flowing fractured zone is analyzed by SPSS software. Based on the data mining tool Weka platform, Bayesian classifier, artificial neural network and support vector machine model are used to mine and analyze the measured data of water flowing fractured zone, and the detailed accuracy, confusion matrix and node error rate are compared. The results show that, the accuracy rate of instance classification of the three models is greater than 60%. The accuracy of the artificial neural network model is the highest and the node error rate is the lowest. In general, the training effect of the artificial neural network model is the best. By predicting engineering examples, the prediction accuracy of the model reaches 80%, and a good prediction effect is obtained. The height prediction system of water flowing fractured zone is developed based on VB language, which can provide a reference for the prediction of the height failure grade of water flowing fractured zone.

Suggested Citation

  • Liyang Bai & Changlong Liao & Changxiang Wang & Meng Zhang & Fanbao Meng & Mingjin Fan & Baoliang Zhang, 2022. "Study on Height Prediction of Water Flowing Fractured Zone in Deep Mines Based on Weka Platform," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:737-:d:1021444
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    References listed on IDEAS

    as
    1. Xing Xu & Xingzhi Wang & Yuanzhi Li & Ning Cao, 2022. "Prediction of the Height of Water Flowing Fractured Zone Based on the MPSO-BP Neural Network Model," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-13, August.
    2. Huiyong Yin & Fangying Dong & Yiwen Zhang & Wenju Cheng & Peihe Zhai & Xuyan Ren & Ziang Liu & Yutao Zhai & Xin Li, 2022. "Height Prediction and 3D Visualization of Mining-Induced Water-Conducting Fracture Zone in Western Ordos Basin Based on a Multi-Factor Regression Analysis," Energies, MDPI, vol. 15(11), pages 1-16, May.
    3. Guojian Zhang & Zhiyang Wang & Guangli Guo & Wei Wei & Fugang Wang & Leilei Zhong & Yaqiang Gong, 2022. "Study on Regional Strata Movement during Deep Mining of Erdos Coal Field and Its Control," IJERPH, MDPI, vol. 19(22), pages 1-32, November.
    4. Yi Tan & Hao Cheng & Wenyu Lv & Weitao Yan & Wenbing Guo & Yujiang Zhang & Tingye Qi & Dawei Yin & Sijiang Wei & Jianji Ren & Yajun Xin, 2022. "Calculation of the Height of the Water-Conducting Fracture Zone Based on the Analysis of Critical Fracturing of Overlying Strata," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
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