Showing 241 - 260 results of 1,333 for search '(((pinn OR (wings OR pinon)) OR fine) OR ((((aina OR ain) OR pannaa) OR (swing OR pingao)) OR pin))', query time: 0.24s Refine Results
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    Data-driven forward and inverse analysis of two-dimensional soil consolidation using physics-informed neural network by Wang, Yu, Shi, Chao, Shi, Jiangwei, Lu, Hu

    Published 2024
    “…Different random seeds are used to test the robustness of the PINN developed and quantify the associated model uncertainty. …”
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    Journal Article
  16. 256

    Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool by Mukhmetov, Olzhas, Zhao, Yong, Mashekova, Aigerim, Zarikas, Vasilios, Ng, Eddie Yin Kwee, Aidossov, Nurduman

    Published 2024
    “…This work presents the development of a novel Physics-Informed Neural Network (PINN) method for fast forward simulation of heat transfer through cancerous breast models. …”
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    Journal Article
  17. 257

    Range expansion of a declining forest species, the Western Gray Squirrel (Sciurus griseus), into semi-arid woodland by Sultaire, SM, Montgomery, RA, Jackson, PJ, Millspaugh, JJ

    Published 2024
    “…The majority of detections were located in piñon–juniper woodland, a land cover type not previously occupied by this species. …”
    Journal article
  18. 258

    Komet by Lim, Guo Jun

    Published 2015
    “…Snow falls, star falls One step, one beginning Two worlds meet one A trail to ever last Butterfly city, never night city Red light, green light Ghosts of thousand faces Beckoning from the wall Good, bad, and ugly Stone ocean, iron sky Omens of million wings The lady fortune frowns So ends the pendulum Farewell goodbye An empty longing For things long gone -In memory of all good things-…”
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    Final Year Project (FYP)
  19. 259

    A comparative analysis of missing data imputation techniques on sedimentation data by Loh, Wing Son, Ling, Lloyd, Chin, Ren Jie, Lai, Sai Hin, Loo, Kar Kuan, Seah, Choon Sen

    Published 2024
    “…A comparative analysis on the missing fine sediment data imputation performance was made based on four different techniques, namely the k-Nearest Neighbourhood (k-NN), Support Vector Regression (SVR), Multiple Regression (MR), and Artificial Neural Network (ANN), under the single imputation (SI) and multiple imputation (MI) regimes. …”
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    Article
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