[1] Rezaei, M., Habibi, H., & Asadizadeh, M. (2024). Determination of the stress concentration factor adjacent an extracted underground coal panel using the CART and MARS algorithms. Earth Science Informatics, 17(6), 5733-5750. https://doi.org/10.1007/s12145-024-01476-3
[2] Majdi, A., Hassani, F. P., & Nasiri, M. Y. (2012). Prediction of the height of destressed zone above the mined panel roof in longwall coal mining. International Journal of Coal Geology, 98, 62-72. https://doi.org/10.1016/j.coal.2012.04.005
[3] National Coal Board. (1975). Subsidence Engineering Handbook. National Coal Board Mining Department.
[4] Munson, D. E., & Eichfeld, W. F., 1980. European empirical methods applied to subsidence in US coal fields (No. SAND-80-1920). Sandia National Labs., Albuquerque, NM (USA).
[5] Karmis, M., Jarosz, A., Schilizzi, P., & Agioutantis, Z. (1987). Surface deformation characteristics above undermined areas: Experience from the Eastern United States. Civil Engineering Transactions, 29(2), 106-114.
[6] Van der Merwe, J. N. (1991). Subsidence caused by high extraction coal mining in the Sasolburg and Secunda areas: prediction thereof and the mitigation of its effects (Doctoral dissertation, PhD thesis, University of the Witwatersrand).
[7] Peng, S. S., Luo, Y., & Zhang, Z. M. (1995). Subsidence parameters-their definitions and determination. PREPRINTS-SOCIETY OF MINING ENGINEERS OF AIME.
[8] Luo, Y., & Peng, S. S. (2000). Prediction of subsurface subsidence for longwall mining operations. In Proceedings of the 19th international conference on ground control in mining (pp. 163-170). West Virginia University, WV.
[9] Cui, X., Wang, J., & Liu, Y. (2001). Prediction of progressive surface subsidence above longwall coal mining using a time function. International journal of Rock Mechanics and Mining Sciences, (38), 1057-1063. https://doi.org/10.1016/S1365-1609(01)00061-2
[10] Alvarez-Fernandez, M., Gonzalez-Nicieza, C., Menendez-Diaz, A., & Alvarez-Vigil, A. (2005). Generalization of the n-k influence function to predict mining subsidence. Engineering Geology, (80), 1-36. https://doi.org/10.1016/j.enggeo.2005.02.004
[11] Asadi, A., Shahriar, K., Goshtasbi, K., & Najm, K. (2005, January). Development of a new mathematical model for prediction of surface subsidence due to inclined coal-seam mining. The Journal of The South African Institute of Mining and Metallurgy.
[12] Keilich, W., Seedsman, R., & Aziz, N. (2006). Numerical Modelling of Mining Induced Subsidence. Coal Operators' Conference, University of Wollongong and the Australasian Institute of Mining and Metallurgy, (pp. 313-326).
[13] Gonzalez-Nicieza, C., Alvarez-Fernandez, M., Menendez-Diaz, A., & Alvarez-Vigil, A. (2007). The infuence of time on subsidence in the Centeral Asturian Coalfield. Bull Eng Geol Environ, (66), 319-329. doi:10.1007/s10064-007-0085-2
[14] Luo, Y., & Cheng, J. (2009). An influence function method-based subsidence prediction program for longwall mining operations in inclined coal seams. Mining Science and Technology (China), 19(5), 592–598. https://doi.org/10.1016/S1674-5264(09)60110-1
[15] Shahriar, K., Amoushahi, S., & Arabzadeh, M. (2009). Prediction of Surface Subsidence Due to Inclined Very Shallow Coal Seam Mining Using FDM. Coal Operators Conference.
[16] Gutierrez, J. J. (2010). Estimating Highway Subsidence due to Longwall Mining. Doctoral dissertation, University of Pittsburgh.
[17] Li, W.-X., Liu, L., & Dai, L.-F. (2010). Fuzzy probability measures (FPM) based non-symmetric membership function: Engineering examples of ground subsidence due to underground mining. Engineering Application of Artificial Intelligence, (23), 420-431. https://doi.org/10.1016/j.engappai.2010.01.003
[18] Song, S., Zhao, X., Xie, J., & Guan, Y. (2011). Grey Correlation Analysis and Regression Estimation of Mining Subsidence in Yu-Shen-Fu Mining Area. Procedia Environmental Sciences, (10), 1747-1752. https://doi.org/10.1016/j.proenv.2011.09.274
[19] Luo, Y., & Qiu, B. (2012). CISPM-MS, a Tool to Predict Surface Subsidence and to Study Interactions Associated with Multi-Seam Mining Operations. In Proceedings of the 31st International Conference on Ground Control in Mining (pp. 56-62). West Virginia University.
[20] Xu, N., Kulatilake, P., Tian, H., Wu, X., Nan, Y., & Wei, T. (2013). Surface subsidence prediction for the WUTONG mine using a 3-D finite difference method. Computers and Geotechnics, (48), 134-145. https://doi.org/10.1016/j.compgeo.2012.09.014
[21] Guo, G., Zhu, X., Zha, J., & Wang, Q. (2014). Subsidence prediction method based on equivalent mining height theory for solid backfilling mining. Trans. Nonferrous Met. Soc. China, (24), 3302-3308. https://doi.org/10.1016/s1003-6326(14)63470-1
[22] Ren, G., Li, G., & Kulessa, M. (2014). Application of a Generalised Influnce Function Method for Subsidence Prediction in Multi-seam Longwall Extraction. Geotech Geol Eng, (32), 1123-1131. https://doi.org/10.1007/s10706-014-9787-y
[23] Howladar, M. F., & Hasan, K. (2014). A study on the development of subsidence due to the extraction of 1203 slice with its associated factors around barapukuria underground coal mining industrial area, Dinajpur, Bangladesh.
Environmental Earth Sciences,
72(9), 3699–3713
. https://doi.org/10.1007/s12665-014-3419-y
[24] Sasaoka, T., Takamoto, H., Shimada, H., Oya, J., Hamanaka, A., & Matsui, K. (2015). Surface subsidence due to underground mining operation under weak geological condition in Indonesia. Journal of Rock Mechanics and Geotechnical Engineering, 7, 337-344. https://doi.org/10.1016/j.jrmge.2015.01.007
[25] Ghabraie, B., Ren, G., Zhang, X., & Smith, J. (2015). Physical modelling of subsidence from sequenttial extraction of partially overlapping longwall panels and study of substrata movement characteristics. International Journal of Coal Geology, (140), 71-83. https://doi.org/10.1016/j.coal.2015.01.004
[26] Suchowerska Iwanec, A. M., Carter, J. P., & Hambleton, J. P. (2016). Geomechanics of subsidence above single and multi-seam coal mining.
Journal of Rock Mechanics and Geotechnical Engineering, 8(3), 304–313.
https://doi.org/10.1016/j.jrmge.2015.11.007
[27] Zhang, B., Zhang, L., Yang, H., Yang, Z., & Tao, J. (2016). Subsidence prediction and susceptibility zonation for collapse above goaf with thick alluvial cover: a case study of the Yongcheng coalfield, Henan Province, China. Bull Eng Geol Environ, 75, 1117-1132. https://doi.org/10.1007/s10064-015-0834-6
[28] Fathi Salmi, E., Nazem, M., & Karakus, M. (2017). Numerical analysis of a large landslide induced by coal mining subsidence. Engineering Geology, (217), 141-152. https://doi.org/10.1016/j.enggeo.2016.12.021
[29] Ghabraie, B., Ren, G., Barbato, J., & V. Smith, J. (2017). A predictive methodology for multi-seam mining induced subsidence. International Journal of Rock Mechanics & Mining Sciences, 93, 280-294. https://doi.org/10.1016/j.ijrmms.2017.02.003
[30] Pongpanya, P., Sasaoka, T., Shimada, T., & Wahyudi, S. (2017). Study of Characteristics of Surface Subsidence in Longwall Coal Mine under Poor Ground Conditions in Indonesia. Earth Science Research, 6(1). https://doi.org/10.5539/esr.v6n1p129
[31] Cheng, J., Liu, F., & Li, S. (2017). Model for the prediction of subsurface strata movement due to underground mining. Journal of Geophysics and Engineering, 14(6), 1608-1623. https://doi.org/10.1088/1742-2140/aa8238
[32] He, C., & Xu, J., (2018). Subsidence prediction of overburden strata and surface based on the voussoir beam structure theory. Advances in Civil Engineering. https://doi.org/10.1155/2018/2606108
[33] Zhang, B., Ye, J., Zhang, Z., Xu, L., & Xu, N., (2019). A comprehensive method for subsidence prediction on two-seam longwall mining. Energies, 12(16), 3139. https://doi.org/10.3390/en12163139
[34] Cui, X., Zhao, Y., Wang, G., Zhang, B., & Li, C. (2020). Calculation of residual surface subsidence above abandoned longwall coal mining. Sustainability, 12(4), 1528. https://doi.org/10.3390/su12041528
[35] Guo, W., Zhao, G., Bai, E., Guo, M., & Wang, Y. (2021). Effect of overburden bending deformation and alluvium mechanical parameters on surface subsidence due to longwall mining. Bulletin of Engineering Geology and the Environment, 80, 2751-2764. https://doi.org/10.1007/s10064-020-02091-4
[36] Pan, R., Li, Y., Wang, H., Chen, J., Xu, Y., Yang, H., & Cao, S., 2021. A new model for the identification of subcritical surface subsidence in deep pillarless mining. Engineering Failure Analysis, 129, 105631. https://doi.org/10.1016/j.engfailanal.2021.105631
[37] Xu, J., Zhu, W., Xu, J., Wu, J., & Li, Y., 2021. High-intensity longwall mining-induced ground subsidence in Shendong coalfield, China. International Journal of Rock Mechanics and Mining Sciences, 141, 104730. https://doi.org/10.1016/j.ijrmms.2021.104730
[38] Yan, Y., Li, M., Liu, J., Yan, W., Zhang, J., & Zhou, B. (2021). Ground subsidence evolution from 1000 m deep mining: a case study in Fengfeng mining area. Shock and Vibration, 2021, 1-9. https://doi.org/10.1155/2021/9942968
[39] Prakash, A., Kumar, A., Verma, A., Mandal, S. K., & Singh, P. K. (2021). Trait of subsidence under high rate of coal extraction by longwall mining: Some inferences. Sādhanā, 46, 1-8. https://doi.org/10.1007/s12046-021-01747-5
[40] Yin, H., Guo, G., Li, H., Wang, T., & Yuan, Y., (2022). Prediction method and research on characteristics of surface subsidence due to mining deeply buried Jurassic coal seams. Bulletin of Engineering Geology and the Environment, 81(10), 449. https://doi.org/10.1007/s10064-022-02946-y
[41] Wang, K., Li, J., & Jin, Z. (2022). Influence of the primary key stratum on surface subsidence during longwall mining. Sustainability, 14(22), 15027. https://doi.org/10.3390/su142215027
[42] Khanal, M., Qu, Q., Zhu, Y., Xie, J., Zhu, W., Hou, T., & Song, S. (2022). Characterization of overburden deformation and subsidence behavior in a kilometer deep longwall mine. Minerals, 12(5), 543. https://doi.org/10.3390/min12050543
[43] Taherdito, A. H., Sulistianto, B., Karian, T., & Widodo, N. P. (2023). Surface Subsidence Prediction Using Numerical Method, Cased Study of Longwall Mining in Indonesia.
[44] Diddle, B., Agioutantis, Z., Maldonado Esguerra, E., Romero Benitez, J. D., & Parra Valencia, M. (2024). Prediction of Dynamic and Final Vertical and Horizontal Movements Due to Longwall Mining. Rock Mechanics and Rock Engineering, 1-18. https://doi.org/10.1007/s00603-024-04262-1
[45] Maldonado, E., Benitez, J. R., & Agioutantis, Z. (2024, June). Sensitivity analysis of a dynamic subsidence prediction model for longwall extraction. In ARMA US Rock Mechanics/Geomechanics Symposium (p. D042S056R001). ARMA. https://doi.org/10.56952/ARMA-2024-0064
[46] Liu, X., Zhang, Y., Zhang, J., Yang, T., Jia, P., & Guo, R. (2024). Modelling surface subsidence of coal mines using a bonded block numerical method. Geomatics, Natural Hazards and Risk, 15(1), 2336017. https://doi.org/10.1080/19475705.2024.2336017
[47] Cheng, G., Liu, H., Li, F., Nie, T., Wang, Q., & Peng, C. (2025). Study on subsidence evolution induced by coal mining under highway based on finite element simulation. Energy Exploration & Exploitation, 01445987241312703. https://doi.org/10.1177/01445987241312703
[48] Rasouli, H., Shahriar, K., & Madani, S. H. (2021). Mine subsidence prediction using gene expression programming based on multivariable symbolic regression. ITEGAM-JETIA, 7(29), 13-24.
[49] خطیبی، ا.، شهریار، ک. (1387). تحلیل نشست سطح زمین در اثر استخراج زغال به روش جبههکار طولانی-مطالعه موردی منطقه زغالدار طبس. دومین کنفرانس مهندسی معدن ایران، دانشگاه تهران، 7 تا 9 آبانماه.
[50] دباغ، ع.، فاتحی مرجی، م.، فرقانی، ح. (1388). شبیهسازی نشست سطح زمین در معادن لایهای شیبدار با استفاده از روش المان مرزی ناپیوستگی در جابجایی. نشریه علمی-پژوهشی مهندسی معدن، دوره 4، شماره 7، صفحه 53 تا 62.
[51] نجفی، م.، عطائی، م. (1391). تخمین میزان نشست سطح زمین در روش جبههکار بلند مکانیزه با استفاده از مدلسازی عددی، مطالعه موردی: معدن زغالسنگ طبس. اولین کنگره ملی زغالسنگ ایران، دانشگاه شاهرود، 8 تا 10 شهریورماه.
[52] Vapnik, V. N. (1995). The nature of statistical learning theory, New York: Springer.
[53] Armaghani, D. J., Koopialipoor, M., Bahri, M., Hasanipanah, M., Tahir, M. M. (2020). A SVR-GWO technique to minimize flyrock distance resulting from blasting. Bulletin of Engineering Geology and the Environment, 79(8): 4369-4385. https://doi.org/10.1007/s10064-020-01834-7
[54] Shi, X. Z., Jian, Z. H. O. U., Wu, B. B., Huang, D., Wei, W. E. I. (2012). Support vector machines approach to mean particle size of rock fragmentation due to bench blasting prediction. Transactions of Nonferrous Metals Society of China, 22(2): 432-441. https://doi.org/10.1016/S1003-6326(11)61195-3
[55] Zhou, J., Li, X., Shi, X. (2012). Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines. Safety science, 50(4): 629-644. https://doi.org/10.1016/j.ssci.2011.08.065
[56] Zhou, J., Qiu, Y., Zhu, S., Armaghani, D. J., Li, C., Nguyen, H., Yagiz, S. (2021). Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate. Engineering Applications of Artificial Intelligence, 97: 104015. https://doi.org/10.1016/j.engappai.2020.104015
[57] Rad, H. N., Hasanipanah, M., Rezaei, M., Eghlim, A. L. (2018). Developing a least squares support vector machine for estimating the blast-induced flyrock. Engineering with Computers, 34: 709-717. https://doi.org/10.1007/s00366-017-0568-0
[58] Vapnik, V. (1999). The nature of statistical learning theory, Springer, Berlin.
[59] Mohammadi-Balani, A., Nayeri, M.D., Azar, A., Taghizadeh-Yazdi, M. (2021). Golden eagle optimizer: A nature-inspired metaheuristic algorithm. Computers & Industrial Engineering, 152, 107050. https://doi.org/10.1016/j.cie.2020.107050
[60] Zhang, P., Wu, H.N., Chen, R.P. and Chan, T.H. (2020). Hybrid meta-heuristic and machine learning algorithms for tunneling-induced settlement prediction: A comparative study. Tunnelling and Underground Space Technology, 99, 103383. https://doi.org/10.1016/j.tust.2020.103383
[61]. Tang, L. and Na, S. (2021). Comparison of machine learning methods for ground settlement prediction with different tunneling datasets. Journal of Rock Mechanics and Geotechnical Engineering, 13(6), 1274-1289. https://doi.org/10.1016/j.jrmge.2021.08.006
[62] Hastie, T., Tibshirani, R., Friedman, J. H., & Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction (Vol. 2, pp. 1-758). New York: springer.
[63] Draper, N. R., & Smith, H. (1998). Applied regression analysis (Vol. 326). John Wiley & Sons. https://doi.org/10.1002/9781118625590
[64] Yagiz, S., Gokceoglu, C., Sezer, E., & Iplikci, S. (2009). Application of two non-linear prediction tools to the estimation of tunnel boring machine performance. Engineering Applications of Artificial Intelligence, 22(4-5), 808-814. https://doi.org/10.1016/j.engappai.2009.03.007
[65] Bezerra, M. A., Santelli, R. E., Oliveira, E. P., Villar, L. S., & Escaleira, L. A. (2008). Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta, 76(5), 965-977. https://doi.org/10.1016/j.talanta.2008.05.019
[66] Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single diagram. Journal of geophysical research: atmospheres, 106(D7), 7183-7192. https://doi.org/10.1029/2000JD900719
[67] Bi, J., & Bennett, K. P. (2003). Regression error characteristic curves. In Proceedings of the 20th international conference on machine learning (ICML-03) (pp. 43-50).
[68] Fattahi, H., & Babanouri, N. (2017). Applying optimized support vector regression models for prediction of tunnel boring machine performance. Geotechnical and Geological Engineering, 35(5), 2205-2217. https://doi.org/10.1007/s10706-017-0238-4
[69] Yang, Y., & Zhang, Q. (1997). A hierarchical analysis for rock engineering using artificial neural networks. Rock mechanics and rock engineering, 30, 207-222. https://doi.org/10.1007/BF01045717
