Prediction of the Dynamic Stiffness of Resilient Materials using Artificial Neural Network (ANN) Technique
High-rise residential buildings are constructed in countries with high population density in response to the need to utilize small development areas. As many high-rise buildings are being constructed, issues of floor impact sound tend to occur in buildings. In general, resilient materials are implem...
Main Authors: | Changhyuk Kim, Jung-Yoon Lee, Moonhyun Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-03-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | http://www.mdpi.com/2076-3417/9/6/1088 |
Similar Items
-
The Prediction of Stiffness of Bamboo-Reinforced Concrete Beams Using Experiment Data and Artificial Neural Networks (ANNs)
by: Muhtar, et al.
Published: (2020-08-01) -
Predicting Long-Term Deformation of Soundproofing Resilient Materials Subjected to Compressive Loading: Machine Learning Approach
by: Seungbum Koo, et al.
Published: (2020-09-01) -
The Prediction of Stiffness Reduction Non-Linear Phase in Bamboo Reinforced Concrete Beam Using the Finite Element Method (FEM) and Artificial Neural Networks (ANNs)
by: Muhtar
Published: (2020-12-01) -
Burnout, Resilience, and COVID-19 among Teachers: Predictive Capacity of an Artificial Neural Network
by: Juan Pedro Martínez-Ramón, et al.
Published: (2021-09-01) -
A Deep Neural Network Model for Short-Term Load Forecast Based on Long Short-Term Memory Network and Convolutional Neural Network
by: Chujie Tian, et al.
Published: (2018-12-01)