Page 118 - 2025年第56卷第8期
P. 118
Methods,2019,166:91 - 102.
[ 9] 吴涛.基于深度森林与分层回归算法的人脸年龄估计方法研究[D].南京:南京大学,2019.
[10] 康文豪,徐天奇,王阳光,等.双层特征选择和 CatBoost - Bagging集成的短期风电功率预测[J].重庆理工
大学学报(自然科学),2022,36(7):303 - 309.
[11] CHENJ,TANGJ,XIAH,etal.Modellingthefurnacetemperaturefieldofamunicipalsolidwasteincinerator
usingthenumericalsimulationandthedeepforestregressionalgorithm [J].Fuel,2023,347:128511.
[12] ZHOUY,CHENJ,YUZJ,etal.Short - termbuildingoccupancypredictionbasedondeepforestwithmulti - or
dertransitionprobability [J].EnergyandBuildings,2022,255:111684.
[13] ZHUX,ZHANG H,REN Q,etal.AnautomaticidentificationmethodofimbalancedlithologybasedonDeep
ForestandK - meansSMOTE[J].GeoenergyScienceandEngineering,2023,224:211595.
[14] 谢军飞,张海清,李代伟,等.基于 Lightgbm和 XGBoost的优化深度森林算法[J].南京大学学报 (自然
科学版),2023,59(5):833 - 840.
[14] CHENT,GUESTRINC.Xgboost:Ascalabletreeboostingsystem[C]??Proceedingsofthe22ndacm sigkddin
ternationalconferenceonknowledgediscoveryanddatamining.2016.
[16] YINL,SUNZ,GAOF,etal.Deepforestregressionforshort - termloadforecastingofpowersystems[J].IEEE
Access,2020,8:49090 - 49099.
[17] LEANDROCSD,AYALAH VH,MARIANIVC.COandNOxemissionspredictioningasturbineusingano
velmodelingpipelinebasedonthecombinationofdeepforestregressorandfeatureengineering[J].Fuel,2024,
355:129366.
[18] NARUEII,KEYNIAF,SABBAGH M A.Hunter - preyoptimization:Algorithm andapplications[J].SoftCom
puting,2022,26(3):1279 - 1314.
[19] 刘相杰,刘小生,张龙威.基于 VMD - HPO - BiLSTM的大坝变形预测[J].大地测量与地球动力学,2023,
43(8):851 - 855.
[20] 许建伟,崔东文.WPT - HPO - ELM径流多步预报模型研究[J].水资源与水工程学报,2022,33(6):69 -
76.
[21] HASSANM H,DAQAQF,KAMElS,etal.Anenhancedhunter - preyoptimizationforoptimalpowerflowwith
FACTSdevicesandwindpowerintegration[J].IETGeneration, Transmission& Distribution,2023.doi:10.
1049?gtdz.12879.
[22] 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.
[23] 江超,张治中,胡正操,等.基于改进的猎食者优化的 D2D通信功率控制方法[J].电子测量技术,2023,
46(6):31 - 36.
[24] LUNDBERCSM,LEESI.Aunifiedapproachtointerpretingmodelpredictions[C]??ProceedingsofAnnualCon
ferenceonNeuralInformationProcessingSystems.2017.
[25] 余红玲,王晓玲,任炳昱,等.土石坝渗流性态分析的 IAO - XGBoost集成学习模型与预测结果解释 [J].
水利学报,2023,54(10):1195 - 1209.
[26] LIL,LIUZ,SHENJ,etal.ALightGBM- basedstrategytopredicttunnelrockmassclassfromTBM construction
dataforbuildingcontrol[J].AdvancedEngineeringInformatics,2023,58:102130.
[27] 杨庆,王春生,刘存,等.抽水蓄能电站地下厂房开挖期通风风量研究[J].水电站设计,2023,39(2):
1 - 4.
[28] 蒋仲安,杨向东.基于环境参数协同预测风速的掘进面智能变频通风控制系统[J].金属矿山,2023(7):
57 - 65.
[29] GUOJ,LIA,WANGT,etal.Parametricmodelingstudyforblown - dustsecondarypollutionandoptimalventi
lationvelocityduringtunnelconstruction [J].EnvironmentalPollution,2023,335:122239.
[30] CHANGX,CHAIJ, LUO J, etal.Tunnelventilationduringconstructionanddiffusionofhazardousgases
studiedbynumericalsimulations[J].BuildingandEnvironment,2020(177):106902.
[31] XIEZ,XIAOY,JIANGC,etal.Numericalstudyonfinedustpollutioncharacteristicsundervariousventilation
timeinmetrotunnelafterblasting [J].BuildingandEnvironment,2021(204):108111.
— 1 0 2 —
8

