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

doi:10.18687/LACCEI2019.1.1.169

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

Departamento Académico de Ingeniería de Sistemas e Informática

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión 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 contribución	Distributed system RNA-Ag for the optimization of design patterns in reinforced concrete beams
Idioma original	Español
Título de la publicación alojada	17th 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
Editorial	Latin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)	9780999344361
DOI	https://doi.org/10.18687/LACCEI2019.1.1.169
Estado	Publicada - 2019
Evento	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica Duración: 24 jul. 2019 → 26 jul. 2019

Serie de la publicación

Nombre	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen	2019-July
ISSN (versión digital)	2414-6390

Conferencia

Conferencia	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
País/Territorio	Jamaica
Ciudad	Montego Bay
Período	24/07/19 → 26/07/19

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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10.18687/LACCEI2019.1.1.169

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Saico, J. S., Acero, P. V., Sanchez, R. T., Concha, H., & Sulla Torres, J. A. (2019). Sistema Distribuido RNA-AG para la Optimización de Patrones de Diseño en Vigas de Concreto Armado. En 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019 (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2019-July). Latin American and Caribbean Consortium of Engineering Institutions. https://doi.org/10.18687/LACCEI2019.1.1.169

Saico, Justo Saico ; Acero, Paul Ventura ; Sanchez, Richard Tumailla et al. / Sistema Distribuido RNA-AG para la Optimización de Patrones de Diseño en Vigas de Concreto Armado. 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions, 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

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title = "Sistema Distribuido RNA-AG para la Optimizaci{\'o}n de Patrones de Dise{\~n}o en Vigas de Concreto Armado",

abstract = "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%.",

keywords = "Artificial Neural Networks, Concurrence, Distributed Evolutionary Algorithm, Genetic Algorithms, Parallelism, Reinforced Concrete Beam Design",

author = "Saico, {Justo Saico} and Acero, {Paul Ventura} and Sanchez, {Richard Tumailla} and Hector Concha and {Sulla Torres}, {Jose Alfredo}",

year = "2019",

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language = "Espa{\~n}ol",

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Saico, JS, Acero, PV, Sanchez, RT, Concha, H & Sulla Torres, JA 2019, Sistema Distribuido RNA-AG para la Optimización de Patrones de Diseño en Vigas de Concreto Armado. En 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2019-July, Latin American and Caribbean Consortium of Engineering Institutions, 17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019, Montego Bay, Jamaica, 24/07/19. https://doi.org/10.18687/LACCEI2019.1.1.169

Sistema Distribuido RNA-AG para la Optimización de Patrones de Diseño en Vigas de Concreto Armado. / Saico, Justo Saico; Acero, Paul Ventura; Sanchez, Richard Tumailla et al.

17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions, 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2019-July).

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Sistema Distribuido RNA-AG para la Optimización de Patrones de Diseño en Vigas de Concreto Armado

AU - Saico, Justo Saico

AU - Acero, Paul Ventura

AU - Sanchez, Richard Tumailla

AU - Concha, Hector

AU - Sulla Torres, Jose Alfredo

PY - 2019

Y1 - 2019

N2 - 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%.

AB - 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%.

KW - Artificial Neural Networks

KW - Concurrence

KW - Distributed Evolutionary Algorithm

KW - Genetic Algorithms

KW - Parallelism

KW - Reinforced Concrete Beam Design

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U2 - 10.18687/LACCEI2019.1.1.169

DO - 10.18687/LACCEI2019.1.1.169

M3 - Contribución a la conferencia

AN - SCOPUS:85073617528

T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology

BT - 17th LACCEI International Multi-Conference for Engineering, Education, and Technology

PB - Latin American and Caribbean Consortium of Engineering Institutions

Y2 - 24 July 2019 through 26 July 2019

ER -

Saico JS, Acero PV, Sanchez RT, Concha H, Sulla Torres JA. Sistema Distribuido RNA-AG para la Optimización de Patrones de Diseño en Vigas de Concreto Armado. En 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions. 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/LACCEI2019.1.1.169

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

Resumen

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