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

Leandro Tortosa (1) , Jose Luis Oliver (2) , Jose Francisco Vicent (1)

1 Ciencia de la Computación e Inteligencia Artificial
2 Expresión Gráfica y Cartografía

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 analyzing and understanding complex urban situations. By the word complex we mean urban concentrations without precise limits and without a recognizable geometry pattern. What we propose is an adaptation of a neural network algorithm to work in the context of urban networks. Our objective is to develop an 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 consisting of a self-organizing algorithm which objective is to generate the positions of the nodes of the simplified mesh. A triangulation algorithm is carried out to reconstruct the triangles of the new simplified mesh. Some real examples of urban actions are shown.

Mots clés: Physical Sciences

Domaines: Informatique [cs]

Leandro Tortosa, Jose Luis Oliver, Jose Francisco Vicent. A neural network model to develop actions in urban complex systems represented by 2D meshes.. International Journal of Computer Mathematics, 2011, 88 (16), pp.3361-3379. ⟨10.1080/00207160.2011.608843⟩. ⟨hal-00744820⟩