EnergySix-legged robot developed in Penza for pipeline inspectionCNews · 3dModellingEnhanced Imitation Learning of Model Predictive Control through Importance WeightingarXiv — Systems and Control (eess.SY) · 4dModellingLimited knowledge exchange across biological subfields in agent-based modellingarXiv — Physics and Society (physics.soc-ph) · 4dDigital twinReasoner-checked ontology crosswalks for a national digital twinarXiv API — полнотекстовый поиск "digital twin" · 5dDigital twinDigital twin speeds up reinforcement learning for lab robotsarXiv API — полнотекстовый поиск "digital twin" · 5dDigital twinDataset for deciding between evidence gathering and action in control-system incidentsarXiv — Computational Engineering, Finance, and Science (cs.CE) · 5dDigital twinSparse stochastic twins can outperform exact digital twinsarXiv — Computational Engineering, Finance, and Science (cs.CE) · 5dModellingPluralism of rival models in network models of sciencearXiv — Multiagent Systems (cs.MA) · 5dForecastingEstimation and MPC for balancing a wheel-legged robot under unknown disturbancesarXiv — Systems and Control (eess.SY) · 5dDigital twinConsolidating dispersed DSO data into a digital twin of the distribution gridarXiv API — полнотекстовый поиск "digital twin" · 6dDigital twinIntegrating ML and uncertainty quantification for real-time decisions in digital twinsarXiv API — полнотекстовый поиск "digital twin" · 6dDigital twinBiases in end-to-end digital twins built from chained modelsarXiv API — полнотекстовый поиск "digital twin" · 5d

Assessing Covariate-Informed Grid Load Forecasting with a Time-Series Foundation Model

US & West · 9 Sept

arXiv:2609.06656v1 Announce Type: cross Abstract: Modern power systems are growing increasingly complex as they integrate diverse generation sources to meet rising demand, making accurate load forecasting challenging.

Original headline: Assessing Covariate-Informed Grid Load Forecasting with a Time-Series Foundation Model

Read the original: arXiv — Systems and Control (eess.SY)

Translation and summary are machine-generated from the source. The full article is not republished; its rights belong to the source.