Results 221 to 230 of about 1,845,449 (415)
Advanced Intelligent Discovery, EarlyView.This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Machine learning models for smart grid stability prediction: a comparative analysis. [PDF]
Sci RepAli AM +3 more
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley +1 more source
Internet of Things-Based Energy Consumption-Aware Framework Design for Smart Grid Environment. [PDF]
Sensors (Basel)Çolak MA, Bayılmış C.
europepmc +1 more source
Three-layer informatics solution for demand response management in the smart grid context
, 2018 Simona‐Vasilica Oprea +2 more
openalex +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Uncertainty Effects on Smart Grid Services for Low-Voltage Distribution Networks. [PDF]
Sensors (Basel)Carere F +4 more
europepmc +1 more source
ENERGY STORAGE, SMART GRID WITH RENEWABLE ENERGY SOURCES
, 2020 V. I. Krasovsky, P. Yatsko
openalex +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Advanced Intelligent Discovery, EarlyView.Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source