Results 101 to 110 of about 96,071 (258)

Graph Neural Network-Based Approach for Detecting False Data Injection Attacks on Voltage Stability

IEEE Open Access Journal of Power and Energy
The integration of information and communication technologies into modern power systems has contributed to enhanced efficiency, controllability, and voltage regulation.
Shahriar Rahman Fahim, Rachad Atat, Cihat Kececi, Abdulrahman Takiddin, Muhammad Ismail, Katherine R. Davis, Erchin Serpedin   +6 more
doaj   +1 more source

Graph Neural Network- Enhanced Power Flow Adjustment

International Journal of Inventive Engineering and Sciences
Modern power grids are facing unprecedented operational complexity due to the surge in distributed energy resources (DERs), intermittent renewables, and electric vehicle (EV) charging demands. While traditional methods like Newton Raphson are computationally precise, their iterative nature often fails to meet the sub-second latency requirements of ...
Gowtham I, Dr. Perumal B
openaire   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

The PRIMA Thesaurus for Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa, Alexey Boubnov, Dario De Angelis, Catriona Eschke, Maximilian Kabbe, Felix Kraus, Mirco Panighel, Richard Thelen, Davide Valentinis   +8 more
wiley   +1 more source

Spatio-Temporal Feature Fusion-Based Hybrid GAT-CNN-LSTM Model for Enhanced Short-Term Power Load Forecasting

Energies
Conventional power load forecasting frameworks face limitations in dynamic spatial topology capture and long-term dependency modeling. To address these issues, this study proposes a hybrid GAT-CNN-LSTM architecture for enhanced short-term power load ...
Jia Huang, Qing Wei, Tiankuo Wang, Jiajun Ding, Longfei Yu, Diyang Wang, Zhitong Yu   +6 more
doaj   +1 more source

Tailoring Functional Properties of Ti–Ni–Cu Shape Memory Alloy Thin Films for MEMS Actuators

Advanced Engineering Materials, EarlyView.
A comprehensive study of critical parameters required to develop well‐performing Ti–Ni–Cu thin film shape memory alloy microactuators is provided. Materials science and device integration aspects are integrated by addressing structural and physical relationships using complementary characterization techniques as well as a practical fabrication solution
Elaheh Akbarnejad, Aleksander Kostka, Gowtham Arivanandhan, Yujiao Li, Alan Savan, Manfred Kohl, Alfred Ludwig   +6 more
wiley   +1 more source

Object-topological modeling of electrical networks

Вестник Северо-Кавказского федерального университета
. Introduction. The Common Information Model (CIM) is the conceptual basis for modeling electrical networks and automating their management. It allows building object-oriented models of electrical networks, but does not provide efficient tools for ...
I. A. Golovinskii
doaj   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

Unveiling the nature of graphs through quantum graphon learning

npj Quantum Information
Graphons are continuous functions hidden behind large-scale graphs. Traditional approaches to graphon learning either suffer from the resolution limitations of piecewise-constant functions or struggle to capture the high-frequency structures intrinsic to
Wenbo Qiao, Peng Zhang, Jiaming Zhao, Shi-Ju Ran   +3 more
doaj   +1 more source

Enhanced thermal modeling of power transformers: A comparison of bond graph and IEEE methods considering external environmental factors

e-Prime: Advances in Electrical Engineering, Electronics and Energy
The optimal and secure operation of electrical power system is largely affected by the reliability of power transformers in operational and economic terms.
Vinit Mehta, Jayashri Vajpai
doaj   +1 more source