Development predictive model of the mechanical properties of soil using artificial neural networks

Authors

DOI:

https://doi.org/10.21501/21454086.4042

Keywords:

Redes neuronales, Perceptrones multicapa, Neuronas prealimentadas;, Propiedades del suelo, Humedad del suelo, Métodos de predicción, Modelos de predicción, Inteligencia artificial, Carreteras, Ingeniería civil

Abstract

Determining soil properties is important in pavement design, for this reason, 4 artificial neural networks based on multilayer Perceptron were developed in this study to predict the maximum dry density (MDD), optimum moisture content (OMC), California bearing ratio (CBR) at 95 % MDD and CBR at 100 % MDD respectively. The method considers a dataset with 285 examples, definition of base architecture through Bayesian optimization and cross-validation, modification of the architecture and hyperparameters to improve performance. The models were trained considering 3000 epochs, RELU function, learning rate, dropout, and were evaluated using the Correlation Coefficient (R) and Mean Squared Error (MSE).
MDD was predicted with R=0,90, OMC with R=0,87, CBR at 95% with R=0,92, CBR at 100% with R=0,89 respectively,
showing that the models are efficient in predicting soil properties.

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Author Biographies

Frank Jesus Valderrama Purizaca, Universidad Señor de Sipán

Bachiller en Ingenieria Civil

Sócrates Pedro Muñoz Pérez, Universidad Señor de Sipan

Ingeniero Civil egresado de la Universidad Nacional Pedro Ruiz Gallo – Lambayeque en el año 2006, con 11 años de experiencia en ejecución de obras civiles y producción de pre fabricados y pretensados y 8 años de colegiado, con grado de Magister en Ciencias de la Tierra con Mención en Geotecnia egresado de la Universidad Nacional de San Agustín – Arequipa, con un Diplomado en Especialización Geología Aplicada en Minería por en la Cámara Minera del Perú. Mis valores primordiales son la lealtad, responsabilidad, compañerismo, la puntualidad y el deseo de superación. Ex Docente de pre grado en los cursos de Mecánica de Suelos, Mecánica de Fluidos, Geología en las Universidad Catolica San Pablo, Universidad Nestor Caceres Velasquez, Universidad Alas Peruanas, Ex Docente de Post Grado de la Universidad Nestor Caceres Velasquez del curso de Mecanica de Suelos y Rocas, Profesor de la Universidad Señor de Sipán

Victor A. Tuesta-Monteza, Universidad Señor Sipan

Ingeniero de Sistemas de la Universidad Señor de Sipán de Perú, 2006, con maestría en Administración de Negocios de la Universidad Cesar Vallejo, Trujillo, Perú, con estudios concluidos de Doctorado en Ciencias de la Educación de la Universidad Señor de Sipán, Chiclayo Perú, Cursando estudios de maestría en Ingeniería de Sistemas con mención en Sistemas de Información en la Universidad Antenor Orrego - Trujillo . Me desempeñé como coordinador de Investigación, Desarrollo e Innovación en el Parque Científico Tecnológico de la Universidad Señor de Sipán, y co-Investigador del proyecto Desarrollo de una herramienta tecnológica para identificación preventiva de deficiencias nutricionales en plantones de café a través de procesamiento de imágenes digitales, financiado por CONCYTEC, Docente en las escuelas profesionales de Ingeniería de Sistemas e Ingeniería Económica de la universidad Señor de Sipán. Actualmente Soy Director de la Escuela Académico Profesional de Ingeniería de Sistemas de la Universidad Señor de Sipan. Trabajo en equipo y me gusta enseñar y aprender de los demás.

Heber Ivan Mejía-Cabrera, Universidad Señor Sipan.

Mg. Heber Ivan Mejia Cabrera, Docente de tiempo completo de la universidad Señor de Sipán, adscrito a la Escuela Académico Profesional de Ingeniería de Sistemas, Director del programa de Ingeniería de Sistemas, de la Facultad de Ingeniería, Arquitectura y Urbanismo. Jefe de laboratorio de Investigación de Sistemas Inteligentes y Seguridad Informática. Áreas temática de investigación en procesamiento de imágenes digitales y Arquitectura Empresarial.

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Published

2021-12-02

How to Cite

Valderrama Purizaca, F. J., Muñoz Pérez, S. P., Tuesta-Monteza, V. A., & Mejía-Cabrera, H. I. (2021). Development predictive model of the mechanical properties of soil using artificial neural networks. Lámpsakos, (26), e–4042. https://doi.org/10.21501/21454086.4042

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Articles of scientific and technological research