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[ 19] LI W,WU Z.  A methodology for dam parameter identification combining machine learning,multi-objective optimi⁃
                                                  .
                      zation and multiple decision criteria[J]  Applied Soft Computing,2022,128:109476.
               [ 20] MAHANIA  S, SHOJAEE  S, SALAJEGHEH  E, et  al.   Hybridizing  two-stage  meta-heuristic  optimization  model
                      with weighted least squares support vector machine for optimal shape of double-arch dams[J]  Applied Soft Comput⁃
                                                                                          .
                      ing,2015,27:205-218.
               [ 21] KHATIBINIA M,KHOSRAVI S. A hybrid approach based on an improved gravitational search algorithm and orthogo⁃
                                                                     .
                      nal crossover for optimal shape design of concrete gravity dams[J]  Applied Soft Computing,2014,16:223-233.
               [ 22] SEYEDPOOR S M,SALAJEGHEH J,SALAJEGHEH E,et al.  Optimum shape design of arch dams for earthquake
                      loading using a fuzzy inference system and wavelet neural networks[J]  Engineering Optimization, 2009, 41(5):
                                                                          .
                      473-493.
               [ 23] ZHANG  M, LI  M, SHEN  Y, et  al.   Isogeometric  shape  optimization  of  high  RCC  gravity  dams  with  functionally
                                                                  .
                      graded partition structure considering hydraulic fracturing[J]  Engineering Structures,2019,179:341-352.
               [ 24] HAMIDIAN  D, SEYEDPOOR  S  M.   Shape  optimal  design  of  arch  dams  using  an  adaptive  neuro-fuzzy  inference
                      system and improved particle swarm optimization[J]  Applied Mathematical Modelling,2010,34(6):1574-1585.
                                                          .
               [ 25] HARIRI-ARDEBILI  M  A, POURKAMALI-ANARAKI  F.   An  automated  machine  learning  engine  with  inverse
                                                  .
                      analysis for seismic design of dams[J]  Water,2022,14(23):3898.
                                                                                                          .
               [ 26] ZHANG J,ZHONG D,WU B,et al.  Earth dam construction simulation considering stochastic rainfall impact[J]
                      Computer Aided Civil and Infrastructure Engineering,2018,33(6):459-480.
               [ 27] DU R,ZHONG D,YU J,et al.  Construction simulation for a core rockfill dam based on optimal construction stages
                      and zones:case study[J]  Journal of Computing in Civil Engineering,2016,30(3):05015002.
                                         .
                                                                               .
               [ 28] 毕磊 .  基于不确定性分析的地下洞室群施工进度仿真分析与优化研究[D]  天津:天津大学,2015.
               [ 29] YU J, ZHONG D, REN B, et al.  Probabilistic risk analysis of diversion tunnel construction simulation[J]  Com⁃
                                                                                                      .
                      puter Aided Civil and Infrastructure Engineering,2017,32(9):748-771.
                                                                                  .
               [ 30] 闫玉亮 .  耦合优化 ICSRAM 和 BBNs 方法的心墙堆石坝施工进度风险分析[D]  天津:天津大学,2017.
               [ 31] 钟登华,张元坤,吴斌平,等 .  基于实时监控的碾压混凝土坝仓面施工仿真可视化分析[J]  河海大学学报
                                                                                               .
                      (自然科学版),2016,44(5):377-385.
               [ 32] GUAN T,ZHONG D H,REN B Y,et al.  Construction simulation of high arch dams based on fuzzy Bayesian updat⁃
                                  .
                      ing algorithm[J]  Journal of Zhejiang University Science A,2018,19(7):505-520.
               [ 33] 钟登华,关涛,任炳昱 .  基于改进重抽样法的高拱坝施工进度仿真研究[J]  水利学报,2016,47(4):473-482.
                                                                              .
               [ 34] 杜荣祥,心墙堆石坝施工智能监控理论与应用研究[D]  天津:天津大学,2017.
                                                                 .
                                                                                      .
               [ 35] 王乾伟 .  基于自适应仿真的高碾压混凝土坝施工进度实时控制理论及应用研究[D]  天津:天津大学,2017.
               [ 36] 肖尧,钟登华,余佳,等.基于改进 HT-LCNN 线段检测模型的隧洞施工活动时间信息智能提取方法[J].水
                      利学报,2024,55(1):24-34,47.
               [ 37] YAO X,JIA Y,GUOXIN X,et al.  An improved BiGAN model for multivariate estimation of correlated and imbal⁃
                      anced tunnel construction parameters[J]  Journal of Rock Mechanics and Geotechnical Engineering,2023,15(7):
                                                    .
                      1797-1809.
               [ 38] ZHANG Y, WANG X, YU J, et al.  Multistep prediction for earthworks unloading duration: a fuzzy Att-Seq2Seq
                      network  with  optimal  partitioning  and  multi-time  granularity  modeling[J]   Neural  Computing  and  Applications,
                                                                              .
                      2023,35(28):21023-21042.
               [ 39] 张君,王金国,余佳,等 .  多模态感知驱动下高堆石坝施工仿真参数集成深度学习模型[J]  水利学报,
                                                                                                 .
                      2022,53(9):1049-1063,1072.
               [ 40] 张君,余佳,任炳昱,等 .  考虑高寒低温影响的高心墙堆石坝仓面施工仿真模型研究[J]  水利学报,2022,
                                                                                            .
                      53(2):200-211.
               [ 41] ZHANG  J, ZHONG  D, ZHAO  M, et  al.   An  optimization  model  for  construction  stage  and  zone  plans  of  rockfill
                      dams based on the enhanced whale optimization algorithm[J]  Energies,2019,12(3):1-29.
                                                                  .
                                                                          .
               [ 42] 吕菲 .  基于机器学习的高心墙堆石坝施工全过程仿真优化研究[D]  天津:天津大学,2024.
               [ 43] 吕菲,钟登华,余佳,等 .  迁移学习框架下高心墙堆石坝施工仿真参数 IGOA-MLP 动态预测模型[J] 水利学
                                                                                                     .
                      报,2023,54(10):1151-1162.
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