Probabilistic Prediction and Assessment of Train-Induced Vibrations Based on Mixture Density Model

Probabilistic Prediction and Assessment of Train-Induced Vibrations Based on Mixture Density Model

This study presents a probabilistic prediction method for train-induced vibrations by combining a deep neural network (DNN) with the mixture density model in a cascade fashion, referred to as the DNN-RMDN model in this paper. A benchmark example is conducted to demonstrate and evaluate the predictio...

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Bibliographic Details
Main Authors: Ziyu Tao, Lingshan He, Desi Tu, Chao Zou
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Buildings
Subjects:
metro depot
train-induced ground vibration
vibration variations
deep learning
residual mixture density network
probabilistic prediction and assessment
Online Access:https://www.mdpi.com/2075-5309/14/11/3468
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