In this plenary talk, the advanced learning process is presented for the original SOR network by employing evaluation-based TRN (topology representing network).
Takeshi Yamakawa, Keiichi Horio, Takahiro Tanaka: Advanced Learning of SOR Network Employing Evaluation-based Topology Representing Network. HIS 2007: 1.
The basic idea behind this framework is to exploit the history data of topology optimization and employ machine learning techniques to discover the underlying ...
Missing: Representing | Show results with:Representing
Apr 11, 2024 · In our proposed method, the density distribution of the multi-scale structure is directly represented by the topology neural network. Report ...
Missing: SOR | Show results with:SOR
Oct 22, 2024 · In the present paper, we propose a new algorithm, namely the Dynamic Topology Representing Networks (DTRN) for learning both topology and ...
Mar 1, 2023 · This paper proposes a novel topology optimization framework: Physics-Informed Neural Network-based Topology Optimization (PINNTO).
The SOR network can obtain the desired input/output relationship of a target system by using the input/output vector pairs and their evaluations. In order to ...
Topology optimization (TO) is a method of deriving an optimal design that satisfies a given load and boundary conditions within a design domain.
Missing: SOR Employing
Jan 6, 2023 · This research proposes a new framework to develop an accurate machine-learning-based surrogate model to predict the optimum topological ...
We will introduce the term masked Voronoi polyhedron and show how these masked Voronoi polyhedra provide a rigorous definition for the terms neighborhood and.
Missing: SOR Evaluation-