A Kolosov-Muskhelishvili informed neural network satisfies plane elasticity equations by construction, achieves sub-1% errors on benchmarks, and uses transfer learning to predict crack paths under multiple criteria with over 70% less training time.
Keijzer, Scaled symbolic regression, Genetic Programming and Evolvable Machines 5 (3) (2004) 259–269
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Merging real-valued GOMEA with GP-GOMEA enables simultaneous optimization of constants and expression structure, generally outperforming other constant-handling techniques in symbolic regression.
citing papers explorer
-
Transfer-learned Kolosov-Muskhelishvili Informed Neural Networks for Fracture Mechanics
A Kolosov-Muskhelishvili informed neural network satisfies plane elasticity equations by construction, achieves sub-1% errors on benchmarks, and uses transfer learning to predict crack paths under multiple criteria with over 70% less training time.