Digital twinSchneider Electric, AVEVA, Nscale and Start Campus pilot AI digital twinEngineering.com · 2dDigital twinLarge Language Models Meet Bayesian Optimization: Towards Self-evolving Wireless Digital TwinsarXiv API — полнотекстовый поиск "digital twin" · 2dModellingJaxMARL-BC: Multi-Agent Reinforcement Learning for Macroeconomic Modelling, in SecondsarXiv — General Economics (econ.GN) · 2dDigital twinDigital Twins of Networked Dynamical Systems: Machine Learning Prediction of Synchronization Transitions in Coupled Chaotic OscillatorsarXiv API — полнотекстовый поиск "digital twin" · 2dDigital twinEvaluating Type-1 Diabetes Digital Twins by Decision QualityarXiv API — полнотекстовый поиск "digital twin" · 2dForecastingCertified Neural Approximation of Robust Nonlinear Model Predictive ControlarXiv — Systems and Control (eess.SY) · 2dForecastingIntegrating Flow Matching and Model Predictive Control for Safe Robot NavigationarXiv — Systems and Control (eess.SY) · 2dForecastingRegion of Attraction Estimation for Linear Quadratic Regulator, Linear and Robust Model Predictive Control on a Two-Wheeled Inverted PendulumarXiv — Systems and Control (eess.SY) · 2dDigital twinVivix Executable Digital Twin for Float GlassSnowflake · 3dDigital twinMicrostructural Generative Inverse Models for Additive Manufacturing Digital TwinsarXiv API — полнотекстовый поиск "digital twin" · 3dModellingCorporate AI in Russia: the bet on agent platformsTAdviser (Telegram) · 3dModellingCorporate AI in Russia: market growth amid unfinished pilotsTAdviser · 3d
Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics
US & West ·
arXiv:2605.12728v2 Announce Type: replace Abstract: The power distribution engineering workforce faces a projected shortage of up to 1.5 million engineers by 2030, creating urgent demand for more accessible analysis tools.
Gasification of Bishkek residential areas will continue from 2028, according to the Kyrgyz parliament speaker citing Gazprom's local subsidiary. Completion of a pipeline from Russia is named as the condition.
A framework builds a wireless V2I digital twin for 6G, exchanging model parameters via compressed personalized federated learning and steering post-reconstruction traffic with LLM-guided multi-agent reinforcement learning. The twin jointly predicts path loss and quality-of-experience KPIs, targeting end-to-end latency reduction in the closed control loop.
arXiv:2610.12909v1 Announce Type: new Abstract: Accurate charging load forecasting is essential for the reliability and efficiency of the Internet of Electric Vehicles (IoEV), yet it is challenging on two fronts: charging demand is highly stochastic, and the data collected by distributed sensors is…