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

Translated title of the contribution: Distributed system RNA-Ag for the optimization of design patterns in reinforced concrete beams

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

Departamento Académico de Ingeniería de Sistemas e Informática

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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%.

Translated title of the contribution	Distributed system RNA-Ag for the optimization of design patterns in reinforced concrete beams
Original language	Spanish
Title of host publication	17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtitle of host publication	"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
Publisher	Latin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)	9780999344361
DOIs	https://doi.org/10.18687/LACCEI2019.1.1.169
State	Published - 2019
Event	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica Duration: 24 Jul 2019 → 26 Jul 2019

Publication series

Name	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume	2019-July
ISSN (Electronic)	2414-6390

Conference

Conference	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
Country/Territory	Jamaica
City	Montego Bay
Period	24/07/19 → 26/07/19

Bibliographical note

Funding Information:
A continuación, el artículo se divide en secciones, como la II donde se mencionan algunos trabajos interesantes relacionados al tema de inteligencia artificial aplicado a construcción de vigas. En la sección III se desarrolla la parte de los materiales usados para la construcción del software, explicamos las diferentes técnicas y tecnologías usadas. En la sección IV se muestran los resultados obtenidos y sus respectivas gráficas de tiempo y validación. Luego la sección V menciona las conclusiones a las que se llegó luego de experimentar la propuesta de RNA-AG paralelizado. En la sección VI de trabajos futuros expresamos nuestro interés por otra técnica de optimización de AE.

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

Access to Document

10.18687/LACCEI2019.1.1.169

Cite this

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. In 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}",

note = "Publisher Copyright: {\textcopyright} 2019 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.; 17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 ; Conference date: 24-07-2019 Through 26-07-2019",

year = "2019",

doi = "10.18687/LACCEI2019.1.1.169",

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booktitle = "17th LACCEI International Multi-Conference for Engineering, Education, and Technology",

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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. in 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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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%.

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KW - Concurrence

KW - Distributed Evolutionary Algorithm

KW - Genetic Algorithms

KW - Parallelism

KW - Reinforced Concrete Beam Design

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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

T2 - 17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019

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. In 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

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