Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Hybrid Physics-Informed Residual Learning for Robust BDS-3 Satellite Clock Bias Prediction. [PDF]
Cheng L +5 more
europepmc +1 more source
Implicit quiescent soliton perturbation in optical metamaterials with complex Ginzburg-Landau equation having nonlinear chromatic dispersion and Kudryashov's forms of self-phase modulation structures by lie symmetry. [PDF]
Adem AR +5 more
europepmc +1 more source
A hybrid analytical-machine learning framework for data-driven modeling of soliton solutions in the complex Ginzburg-Landau equation. [PDF]
Muhammad J, Tedjani AH, Yao F, Younas U.
europepmc +1 more source
Soliton solutions for the nonlinear Zoomeron equation applying the modified Khater method. [PDF]
Saleem A +5 more
europepmc +1 more source
A novel hybrid explainable artificial intelligence modelling approach for smart manufacturing. [PDF]
Abhilash PM, Luo X, Liu Q, Qin Y.
europepmc +1 more source
Ambiguity and free will: the topology of decision in quantum and quantum-like sciences. [PDF]
Plotnitsky A.
europepmc +1 more source

