Page 132 - 《水资源与水工程学报》2025年第1期
P. 132

2
             1 8                      & ' ( ) & * + , -                 2025 $
            [19]WUPin,SUNJunwu,CHANGXuting,etal.Datadriv         n,2008,39(12):13901394+1400.
                 enreducedordermodelwithtemporalconvolutionalneural  [26]) *, xj*. %ƒ VMD-LSSVM{U5JЩðñ
                 network[J].ComputerMethodsinAppliedMechanics      [J]. FU¢1¢³a00n,2023,55(6):10331043.
                 andEngineering,2020,360:112766.               [27]iO[, è (, zw&, :. oØ SBFEMc PSO-LSS
            [20]WANRenzhou,MEIShuping,WANGJun,etal.Multi          VM{7¬è?'<./VÑi÷Ё…€[J].
                 variatetemporalconvolutionalnetwork :adeepneuralnet  Õ%&cCD#00n,2023,31(4):894905.
                 worksapproachformultivariatetimeseriesforecasting  [28]—RÏ, 4H. a<c<%89b¾„螀\I
                 [J].Electronics,2019,8(8):876.                    Õ[M]. FU: E9a0#t,2006.
            [21]HEKaiming,ZHANGXiangyu,RENShaoqing,etal.       [29]LIWenlin,JIANGXuchu.Predictionofairpollutantcon
                 Deepresiduallearningforimagerecognition[C]//2016  centrationsbasedonTCN-BiLSTM -DMAttentionwith
                 IEEEConferenceonComputerVisionandPatternRecog    STLdecomposition[J].ScientificReports,2023,13
                 nition(CVPR).LasVegas:IEEE,2014:770778.          (1):4665.
            [22]XUANBona,LIJin,SONGYafei.SFCWGAN-BiTCN         [30]ZHAOWentian,GAOYanyun,JITingxiang,etal.Deep
                 withsequentialfeaturesformalwaredetection[J].Ap  temporalconvolutionalnetworksforshorttermtrafficflow
                 pliedSciences ,2023,13(4):2079.                   forecasting [J].IEEEAccess,2019,7:114496114507.
            [23]x*5, ) ñ, ) j, :. %ƒ Attention-BiTCN{¶         [31]9aG, ƒ H, é W, :. %ƒdX/[qúû{»
                 ·çÙGñ€[J]. úû¶·89,2024,24(2):309                åÏ@ðñ [J]. ¸¹pCDc¸,2021,42(8):
                 318.                                              22242231.
            [24]iå…, 5„Ê, ¨ R, :. %ƒ\ٔqډ'øÌ                  [32]H±, )_, ƒ–±, :. %ƒ SinGANc LSTM-
                 µŸ¶·{ST¾0iST[J]. ˆ‰UÄa00n                        FCN{q'ú&€Ùü†¦gbñíêÃ^cÞßø
                 ( wx#0t),2024,52(2):111120.                      ‚€[J/OL]. žpq'a00n ( wx#0t),
            [25]9 î, —RÏ, 9áŸ, :. %ƒòz–_Iœ±žz                      2024:110[20240807].http://kns.cnki.net/kcms/de
                 –_I¤¡Ôp{a<½Jb¾iº[J]. Zb0                         tail/13.1212.tm.20240806.1621.002.html.


            檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵檵
              ( LMA 117 B)                                     [41]4žò, ,äÞ, sZÓ. ´ÂõþRÛÆf×ä˜/
            [36]HOSSEINIANSM,GHAHARISM.Therelationshipbe          D89[{?———Îwô¡Ÿ ¨{ê[J]. Ÿ 4
                 tweenstructuralparametersandwaterfootprintofresiden  „,2022,42(6):121131.
                                                               [42]9Á~, s¤¤. %ƒrÌíê{4!›Z¼‚û?Ï
                 tialbuildings [J].JournalofCleanerProduction,2020,
                 279(12):123562.                                  MN{pµ¶[J]. pUdea00n( ‘#0
            [37]LAZARICN,LONGHIC,THOMASC.Gatekeepersof             t),2017,16(2):5056.
                 knowledgeversusplatformsofknowledge :from potential  [43]zú¦. %ƒrÌZÉiº{EFfNò9\¼‚]
                                                                   ´{MNAB[D]. _`: EFa0,2023.
                 torealizedabsorptivecapacity[J].RegionalStudies,
                 2008,42:837852.                              [44]²óô, z^l, ) ë. ô¡Ÿ ¨/D89ZìÏ1
                                                                   µ7Â7cMNQÞ[J]. ô¡JK]^chk,2023,
            [38]ƒ à, )»P, )'F. %ƒZ]^®Ëµ¶{Epf›
                 Z¼89ǂ[J]. Ÿ 4„,2014,34(11):6973+106.            32(9):18221833.
                                                               [45]zõö, ôúµ. ªË45œ›Ÿ ý°õþR‚hk
            [39]HANSENBE.Thresholdeffectsinnondynamicpanels:
                                                                   {Ñ{MN\1Î67AB[J]. SŸ ,2023,39
                 estimation,testing,andinference[J].JournalofEcono
                 metrics,1999,93(2):345368.                       (11):8793+127.
                                                               [46]\î’, œeÊ, ij_. S°Ñ§õþR‚û?Ï
            [40]­’Ú, ¾Yn, F*4, :. ô¡Ÿ ¨»åc´Âõ
                 {5ÒþR\‚´Âõè,{Ñ{MN[J]. ô¡JK                        {Ñ{MN: %ƒô¡Ÿ ¨ 108 f›œ‰õíê{
                                                                   µ¶[J]. ]^#0,2023,45(1):3147.
                 ]^chk,2023,32(5):895904.
   127   128   129   130   131   132   133   134   135   136   137