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A model to simplify 2d triangle meshes with irregular shapes

APPLIEd MATHEMATICS ANd COMPUTATION 2010年第10期216卷 2937-2946页

作者： Tortosa, L. Vicent, J. F. Zamora, A. Univ Alicante Dept Ciencia Computac & Inteligencia Artificial E-03080 Alicante Spain

We present a 2d triangle mesh simplification model which is able to produce high quality approximations of any original planar mesh, regardless of the shape of the original mesh. This method consists of two phases: a self-organizing algorithm and a triangulation algorithm. The self-organizing algorithm is an unsupervised incremental clustering algorithm which provides us a set of nodes representing the best approximation of the original mesh. The triangulation algorithm reconstructs the simplified mesh from the planar points obtained by the self-organizing training process. Some examples are detailed with the purpose of demonstrating the ability of the model to perform the task of simplifying an original mesh with irregular shape. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Algorithm analysis Mesh simplifications Artificial neural networks Triangulation gng3d model Self-organizing systems

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A neural network model to develop actions in urban complex systems represented by 2d meshes

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2011年第16期88卷 3361-3379页

作者： Oliver, Jose L. Tortosa, Leandro Vicent, Jose F. Univ Alicante Dept Ciencia Computac & Inteligencia Artificial E-03080 Alicante Spain

The main idea of this work is to present a tool which may be useful to generate a mesh of points where urban actions may be taken after analysing and understanding complex urban situations. By the word complex we mean urban concentrations without precise limits and without a recognizable geometry pattern. In these situations, it is very hard for the architects to understand the system. Therefore, it is very difficult to define an action plan for this type of urban situations. What we propose is an adaptation of a neural network algorithm to work in the context of urban networks. Our objective is to develop a strategy to change this weakness of sparse urban development by activating public spaces with new meanings. A new 2d triangle mesh simplification model is introduced with the central property of preserving the shape of the original mesh. The mathematical model presented consists of a self-organizing algorithm whose objective is to generate the positions of the nodes of the simplified mesh;afterwards, a triangulation algorithm is carried out to reconstruct the triangles of the new simplified mesh. With this algorithm, it is possible to perform specific actions in an urban space, because the urban territory can be considered as a complex mesh with nodes and edges. A real example of an urban action is shown with the introduction of a wireless network in a residential area.

关键词： submission instructions source file coding artificial neural networks urban systems mesh simplifications triangulation gng3d model urban density

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