AI 용어집
인공지능 완전 사전
Multi-scale reinforcement learning algorithms
Reinforcement learning methods adapted to optimize transition decisions between different resolution scales in complex physical simulations.
AI-assisted domain decomposition methods
Techniques using artificial intelligence to intelligently partition the simulation domain and manage interfaces between multi-scale subdomains.
Hierarchical co-simulation
Structured approach where multiple simulators operating at different scales exchange information in a coordinated manner to represent a complete physical system.
Multi-resolution graph neural networks
Neural network architecture capable of processing structured data at multiple spatial and temporal resolution levels simultaneously.
Learning-enhanced homogenization
Mathematical method combining traditional homogenization techniques with machine learning to efficiently capture multi-scale effects.
Scale transfer learning
Technique enabling the transfer of knowledge learned at one simulation scale to another scale to accelerate convergence and improve accuracy.
AI-guided adaptive meshing
Computational mesh optimization process where artificial intelligence identifies regions requiring finer resolution based on the physics of the problem.
Multi-level model reduction
Set of techniques aimed at reducing computational complexity while preserving the multi-scale fidelity of the original physical model.
Intelligent micro-macro coupling
Integration method between microscopic and macroscopic simulations using AI to optimize information exchange and maintain physical consistency.
Supervised numerical zoom
Technique enabling dynamic zooming into regions of interest within the simulation using learning algorithms to guide resolution.
Evolutionary multi-scale parameterization
Model parameter optimization method that dynamically adapts according to the active resolution scale and the state of the simulated system.
Multi-scale PINNs
Physics-informed neural networks designed to solve partial differential equations representing phenomena at multiple scales simultaneously.
Adaptive temporal decomposition
Temporal discretization technique where the time step is dynamically adapted according to active time scales and guided by AI algorithms.
Intelligent spatial interpolation
Interpolation methods using machine learning to reconstruct physical fields between different spatial resolutions in a consistent manner.
Optimal resolution selection
AI algorithm determining the optimal spatial and temporal resolution for each region of the domain based on precision objectives and computational cost.
Smooth scale transition
Method ensuring a gradual and artifact-free transition between different resolution scales in the simulation by learning transfer functions.
Quantification d'incertitude multi-niveaux
Approche propagant les incertitudes à travers différentes échelles de modélisation en utilisant des techniques d'apprentissage pour estimer les distributions de probabilité.
Transformeurs pour simulations multi-échelles
Architecture basée sur les mécanismes d'attention pour capturer les dépendances à longue portée entre différentes échelles spatiales et temporelles.
Détection de singularités multi-résolution
Algorithme identifiant les points critiques du système nécessitant une résolution accrue à travers plusieurs niveaux d'échelle simultanément.
Parallélisation hétérogène intelligente
Stratégie de distribution computationnelle optimisée par IA pour exploiter efficacement les architectures matérielles hétérogènes dans les simulations multi-échelles.