Numerical grid generation: foundations and applications
Numerical grid generation: foundations and applications
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
On the use of self-organizing maps for clustering and visualization
Intelligent Data Analysis
Neural network approach for parallel construction of adaptive meshes
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
Self-organizing approach to moving surface reconstruction
ISCGAV'09 Proceedings of the 9th WSEAS international conference on Signal processing, computational geometry and artificial vision
Parallel construction of moving adaptive meshes based on self-organization
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
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A neural network approach for the adaptive mesh construction based on Kohonen’s Self-Organizing Maps (SOM) is considered. The approach belongs to a class of methods in which an adaptive mesh is a result of mapping of a computational domain onto a physical domain. There are some imperfections in using the SOM for mesh construction in a pure form. The composite algorithm to overcome these imperfections is proposed. The algorithm is based on the idea to alternate mesh construction on the border and inside the physical domain and includes techniques to control the consistency between boundary and interior mesh nodes and to provide an appropriate distribution of boundary nodes along the border of the domain. To increase the quality and the speed of mesh construction, a number of experiments are held to improve the learning rate. It has been shown that the quality of meshes constructed using the proposed algorithm is admissible according to the generally accepted quality criteria for finite difference meshes.