Determining an approximate finite element mesh density using neural network techniques

IEEE Transactions on Magnetics

Volumn 28, Issue 2, 1992, Pages 1767-1770

  Dyck, D N ^a   Lowther, D A ^a   McFee, S ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; ANALYSIS; FINITE ELEMENT METHOD; NEURAL NETWORKS;

ADAPTIVE SOLVERS; FINITE ELEMENT MESH DENSITY;

MAGNETIC DEVICES;

EID: 0026826870     PISSN: 00189464     EISSN: 19410069     Source Type: Journal    
DOI: 10.1109/20.124047     Document Type: Article

References (4)

1. P. Fernandes, P. Girdinio, P. Molfino and M. Repetto, “An enhanced error estimator procedure for finite element field computation with adaptive mesh refinement,” IEEE Transactions on Magnetics, vol. 26, no. 5, September 1990, pp. 2187–2189.
2. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning Internal Representations by Error Propagation,” Parallel Distributed Processing Vol. 1, MIT Press, Cambridge, 1987, pp. 318–362.
3. P. J. 13. Hancock, “Data Representation in Neural Networks: an Empirical Study,” Proceedings of the 1988 Connectionist Models Summer School, eds. D. Touretzky, G. Hinton, T. Sejnowski, pp. 11–20.
4. D. N. Dyck, Determining Finite Element Mesh Density from Problem Specification using Neural Networks, Master's Thesis, Department of Electrical Engineering, McGill University, November 1990.