A neural network model to develop urban acupuncture

  • Authors:

  • Leandro Tortosa;José F. Vicent;Antonio Zamora;José L. Oliver

  • Affiliations:

  • Departamento de Ciencia de la Computación e Inteligencia Artificial Universidad de Alicante, Alicante, Spain;Departamento de Ciencia de la Computación e Inteligencia Artificial Universidad de Alicante, Alicante, Spain;Departamento de Ciencia de la Computación e Inteligencia Artificial Universidad de Alicante, Alicante, Spain;Departamento de Expresión Grafica y Cartografia, Universidad de Alicante, Alicante, Spain

  • Venue:
  • KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
  • Year:
  • 2010

  • A neural network algorithm to simplify 2D meshes

    ICANCM'11/ICDCC'11 Proceedings of the 2011 international conference on applied, numerical and computational mathematics, and Proceedings of the 2011 international conference on Computers, digital communications and computing

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Abstract

The urban world of the 21st century is composed of numerous nodes, streams and webs, which create a new landscape of globalization and impose different logic of space and time perception. Therefore, the urban infrastructure is updated and its networks are continuously multiplied. A method known as urban acupuncture on the one hand tests the local effects of every project, and on the other hand establishes a network of points or dots to act upon. The main objective of this paper is to relate the concept of urban acupuncture with the use of a neural network algorithm to determine those points where developing actions in order to improve the quality life in cities. We apply the neural network model GNG3D to the design of a simplified network in a real city of our surrounding.