Artificial Neural Model based on radial basis function networks used for prediction of compressive strength of fiber-reinforced concrete mixes

Existe una relación compleja y no lineal entre los factores que influyen en la resistencia de diseño y la compresión de hormigones reforzados con fibras de acero. La relación entre las variables de entrada, los factores y la variable de salida, y la resistencia de diseño...

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Bibliographic Details
Main Authors:	Luis Octavio González Salcedo, Aydee Patricia Guerrero Zúñiga, Silvio Delvasto Arjona, Adrián Luis Ernesto Will
Format:	Article
Language:	English
Published:	Editorial Neogranadina 2019-06-01
Series:	Ciencia e Ingeniería Neogranadina
Subjects:	Hormigón reforzado con fibras resistencia a la compresión predicción de propiedades redes neuronales artificiales funciones de base radial inteligencia artificial
Online Access:	https://revistas.unimilitar.edu.co/index.php/rcin/article/view/3737

Artificial Neural Model based on radial basis function networks used for prediction of compressive strength of fiber-reinforced concrete mixes by Luis Octavio González Salcedo, Aydee Patricia Guerrero Zúñiga, Silvio Delvasto Arjona, Adrián Luis Ernesto Will

Published 2019-06-01

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Artificial Neural Model based on radial basis function networks used for prediction of compressive strength of fiber-reinforced concrete mixes

Artificial Neural Model based on radial basis function networks used for prediction of compressive strength of fiber-reinforced concrete mixes by Luis Octavio González Salcedo, Aydee Patricia Guerrero Zúñiga, Silvio Delvasto Arjona, Adrián Luis Ernesto Will

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