Hybrid Decision Framework Combines Topology and Neural Networks for Industrial Safety
A new hybrid decision-making model combines topological structures and neural networks to improve safety assessments in chemical storage facilities.
A new hybrid decision-making model combines topological structures and neural networks to improve safety assessments in chemical storage facilities.
Researchers have developed a diagnostic framework combining persistent homology and machine learning that detects COVID-19 in chest computed tomography scans ...
Published in Applied Network Science, the study leverages a validated dataset of 336 topology snapshots spanning from January 2019 to ...
Researchers in Chennai show that modified reverse degree graph descriptors, bond-wise entropy, and regression models can accurately predict graph energy ...
Nuclear magnetic resonance measurements reveal three distinct superconducting phases in K₂Cr₃As₃, establishing the compound as a tunable bulk platform for ...
New simulations of the Su–Schrieffer–Heeger model separate two distinct mechanisms of topological qubit protection, showing that chiral symmetry sets the ...
The publication of this framework in Frontiers in Physics arrives at a moment when the experimental foundations of the equivalence ...
© 2026 Scienmag - Science Magazine
© 2026 Scienmag - Science Magazine