Sistema Distribuido RNA-AG para la Optimización de Patrones de Diseño en Vigas de Concreto Armado

Justo Saico Saico, Paul Ventura Acero, Richard Tumailla Sanchez, Hector Concha, Jose Alfredo Sulla Torres

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In this paper, a software system for designing reinforced concrete beams (constrained by its bending and shear force) is built, to show results quickly and accurately, using two Artificial Intelligence techniques: Artificial Neural Networks (ANN) and Genetic Algorithms (GA) and a Distributed Systems model: Master-Slave. The calculation of the optimal weights by using distributed parallelism is achieved by Java RMI, sockets and threads. The purpose of the System presented here is to obtain a NN that is capable of relate historic data used for the design of a beam (cantilever beam, reinforcing steel area, stirrup spacing) and that employs empiric design patterns on similar reinforced concrete beams from Escuela Profesional de Ingenieria Civil (EPIC) at Universidad Nacional de San Agustin (UNSA), Arequipa-Peru. The results are shown in diagrams comparing convergence times using our model and finally concluding its superior efectiveness of speed. For example for populations close to a million, the time is acceptable and the error rate is less than 1%.

Título traducido de la contribuciónDistributed system RNA-Ag for the optimization of design patterns in reinforced concrete beams
Idioma originalEspañol
Título de la publicación alojada17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtítulo de la publicación alojada"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
EditorialLatin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)9780999344361
DOI
EstadoPublicada - 2019
Evento17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica
Duración: 24 jul. 201926 jul. 2019

Serie de la publicación

NombreProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen2019-July
ISSN (versión digital)2414-6390

Conferencia

Conferencia17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
País/TerritorioJamaica
CiudadMontego Bay
Período24/07/1926/07/19

Nota bibliográfica

Publisher Copyright:
© 2019 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

Palabras clave

  • Artificial Neural Networks
  • Concurrence
  • Distributed Evolutionary Algorithm
  • Genetic Algorithms
  • Parallelism
  • Reinforced Concrete Beam Design

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