Results 131 to 140 of about 14,465 (269)

Addressing lightning and market uncertainties in self-scheduling: A fuzzy-markov approach for smart grids. [PDF]

Sci Rep
Benistan IS, Shahbazzadeh MJ, Eslami M.
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

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, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Detection of disturbances and cyber-attacks in smart grids using explainable machine learning. [PDF]

Sci Rep
Farsi M, Alwateer M, Alsaedi SA, AlSahafi AI, Balaha HM, Aboelnaga MM, Badawy M, Elhosseini MA.   +7 more
europepmc   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

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

Attentional LSTM-ensemble architecture for intrusion detection in smart grids. [PDF]

Sci Rep
Singh R, Singh Gill N, Gulia P.
europepmc   +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

Expression of Concern: Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. [PDF]

PLoS One
PLOS One Editors.
europepmc   +1 more source

Energy-Efficient LoRa Routing for Smart Grids. [PDF]

Sensors (Basel), 2023
Repuri RK, Darsy JP.
europepmc   +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, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

Sampled-data control under time-varying delays: a robust approach for high-renewable smart grids. [PDF]

Sci Rep
Hassan M.
europepmc   +1 more source