| [1] 余国锋, 袁亮, 任波, 等. 底板突水灾害大数据预测预警平台[J]. 煤炭学报, 2021, 46(11): 3502-3514.YU Guofeng, YUAN Liang, REN Bo, et al. Big data prediction and early warning platform for floor water in rush disaster[J]. Journal of China Coal Society,2021,46(11): 3502-3514.[2] Li Junqiang, Wang Xiaoshan, Cong yu, et al. Prediction of Water Inflow in Deep Mining of Large Water Mine Based on Visual MODFLOW[J]. METAL MINE, 2024, (10): 257-264.[3] 李建林, 高培强, 王心义, 等. 基于混沌-广义回归神经网络的矿井涌水量预测[J]. 煤炭科学技术, 2022, 50(4): 149-155.LI Jianlin, GAO Peiqiang, WANG Xinyi, et al. Prediction of mine water inflow based on Chaos-Generalized Regression Neural Network[J]. Coal Science and Technology,2022,50(4) :149-155[4] 吴兵, 娄鹏, 王超. 基于Q-S曲线法预测工作面涌水量[J]. 矿业安全与环保, 2014, 41(6): 48-52.WU Bing, LOU Peng, WANG Chao. Prediction of Mine Water Inflow in Working Face Based on Q - S Curve Method[J]. MINING SAFETY & ENVIRONMENTAL PROTECTION,2014,41(6):48–52.[5] 刘兴雷, 吴顺川, 韩龙强, 等. 露天矿地下涌水模拟与安全防治研究[J]. 矿业研究与开发, 2024, 44(2): 151–156.LIU Xinglei, WU Shunchuan, HAN Longqiang, et al. Studyon Simulation and Safety Preventionof Underground Water Inflowin Open-Pit Mine[J]. Mining Research and Development,2024,44(2):151–156.[6] 蔡 磊, 田学军. 基于MODFLOW的某高速公路隧道涌水量预测研究[J]. 青海交通科技, 2022,3 4(2): 128-135.Cai Lei, Tian Xuejun. Research on water inrush prediction of a highway tunnel based on MODFLOW[J]. Qinghai Transportation Science and Technology, 2022, 34(2): 128-135.[7] 谢婷婷. Visual MODFLOW对某磷矿开采矿坑涌水量的预测研究[D]. 成都: 西南交通大学, 2016.[8] XIE Wenchao, REN Bozhi, HURSTHOUSE Andrew, et al. Simulation of manganese transport in groundwater using Visual MODFLOW: a case study from Xiangtan Manganese Ore Area in Central China[J]. Polish Journal of Environmental Studies, 2021, 30(2): 1409-1420.[9] 丁莹莹, 尹尚先, 连会青, 等. 基于CEEMDAN和改进的混合时间序列模型工作面涌水量预测研究[J]. 中国安全生产科学技术, 2024, 20(3): 110-117.DING Yingying, YIN Shangxian, LIAN Huiqing et al. Research on water inflow prediction of working face based on CEEMDAN and improved hybrid time series model[J]. Journal of Safety Science and Technology, 2024, 20(3): 110-117.[10] 连会青, 李启兴, 王瑞, 等. 基于深度学习的LSTM-GRU复合模型矿井涌水量预测方法研究[J]. 煤矿安全, 2024, 55(09): 166-172.LIAN Huiqing, LI Qixing, WANG Rui, et al. Research on mine water inflow prediction method of LSTM-GRU composite model based on deep learning[J], Safety in Coal Mines, 2024, 55(9): 166-172[11] 李占利, 邢金莎, 靳红梅, 等. 基于CEEMD_GRU模型的矿井涌水量预测[J]. 北京工业大学学报, 2021, 47(8): 904-911.LI Zhanli，XING Jinsha，JIN Hongmei, et al. Prediction of Mine Water Inflow Based on CEEMD_GRU Mode[J]. Journal of Beijing University of Technology, 2021, 47(8): 904-911.[12] 乔美英, 程鹏飞, 刘震震. 基于GA-SVM的矿井涌水量预测[J]. 煤田地质与勘探, 2017, 45(6): 117-122.QIAO Meiying, CHENG Pengfei, LIU Zhenzhen. Mine water inflow prediction based on GA-SVM. Coal Geology & Exploration[J] ,2017,45(6):117-122.[13] 侯恩科, 夏冰冰, 吴章涛, 等. 基于CEEMDAN-BO-BiGRU的矿井涌水量预测研究[J]. 科学技术与工程, 2023, 23(28): 12012-12019.HOU Enke, XIA Bingbing, WU Zhangtao, et al. Mine water inflow prediction based on CEEMDAN?BO?BiGRU[J]. Science Technology and Engineering, 2023, 23(28): 12012?12019[14] 马宏忠, 肖雨松, 孙永腾, 等. 基于ICEEMDAN和时变权重集成预测模型的变压器油中溶解气体含量预测[J]. 高电压技术, 2024, 50(1): 210-220.MA Hongzhong, XIAO Yusong, SUN Yongteng, et al. Prediction of Dissolved Gas Concentration in Transformer Oil Based on ICEEMDAN and Time-varying Weight Integrated Prediction Model[J]. High Voltage Engineering, 2024, 50(1): 210-220.[15] 薛建凯. 一种新型的群智能优化技术的研究与应用: 麻雀搜索算法[D]. 上海: 东华大学, 2020.[16] 鞠景会, 赵维刚, 田秀淑, 等. 基于VMD的隧道空洞小波包能量熵提取方法研究[J]. 振动与冲击, 2024, 43(22): 199-208.JU Jinghui，ZHAO Weigang，TIAN Xiushu, et al. Wavelet packet decomposition energy entropy extraction method for the tunnelvoid desease based on VMD[J]. Journal of Vibration and Shock, 2024, 43(22): 199-208.[17] CHEN Yujia., WANG Jianlan, CHEN Weidong, et al. Fault diagnosis in hydropower units based on chaotic Kepler optimization algorithm-enhanced BiLSTM model[J]. Energy Reports, 2024, 12: 5163-5176[18] Dawood, K., & Kül, S. Influence of core window height on thermal characteristics of dry-type transformers[J]. Case Studies in Thermal Engineering, 2025,105746.[19] 朱宇伟,王朋飞,王慧娴,等.基于经验模态分解线性模型的矿压预测[J].煤炭科学技术,2024,52(11):223-232.ZHU Yuwei，WANG Pengfei，WANG Huixian，et al. Mine pressure prediction based on empirical mode decomposi-tion linear model[J]. Coal Science and Technology，2024，52（11）：223?232.[20] 许越,李强,崔晖.基于MIC-EEMD-改进Informer的含高比例清洁能源与储能的电力市场短期电价多步预测[J].电网技术,2024,48(03):949-958.XU Yue,LI Qiang,CUI hui. Short-term Multi-step Price Prediction for the Electricity Market With a High Proportion of Clean Energy and Energy Storage Based on MIC-EEMD-improved Informer[J]. Power System Technology,2024,48(03):949-958.[21] 江莉,向世召.基于CEEMDAN-VSSLMS的滚动轴承故障诊断[J].计算机集成制造系统,2024,30(03):1138-1148.JIANG Li,Xiang Shizhao.RollingbearingfaultdiagnosisbasedonCEEMDAN-VSSLMS[J].Computer Integrated Manufacturing Systems,2024,30(03):1138-1148.[22] Fang S, Chen Y, Wu X, et al. Radon exhalation rate prediction and early warning model based on VMD-GRU and similar day analysis[J]. Journal of Environmental Radioactivity, 2025, 281: 107593.[23] Thangamalar J B, Gomathi R, Gopalakrishnan S, et al. A two-stage linearized model for thermistor circuit linearization using LSTM based multi-layer self-attention model[J]. Measurement, 2025: 116733. |
