Path planning of intelligent driving vehicles in emergencies is a hot research issue, this
paper proposes a new method of the best path selection for the intelligent driving vehicles to …

The application of data science technologies in geotechnical and earthquake engineering is
a hot topic. This study aimed to identify the macroscopic dynamic properties of the soil from …

Hydraulic quantities governing the generation of bedforms (formed spontaneously on the
bottoms of rivers) have been investigated through geomorphological methods, laboratory …

This work proposes a method for estimating dynamics on graph by using dynamic mode
decomposition (DMD) and sparse approximation with graph filter banks (GFBs). The …

Dictionary methods for system identification typically rely on one set of measurements to
learn governing dynamics of a system. In this paper, we investigate how fusion of output …

In this paper, we consider the problem of learning a predictive model for population cell
growth dynamics as a function of the media conditions. We first introduce a generic data …

In channelized alluvial rivers, alternating sandbars are formed by alternating scouring and
sedimentation in the downstream direction. The conditions for the occurrence of sandbars …

This work proposes a novel formulation of convolutional-sparse-coded dynamic mode
decomposition (CSC-DMD) incorporating a deep learning framework. CSC-DMD is a high …

This chapter delves into the utilization of reduced order models (ROMs) for assessing
system performance in geotechnical engineering, specifically focusing on robustness and …

This study applies a variant approach of dynamic mode decomposition (DMD), a multi-
resolution convolutional-sparse-coded DMD (MR-CSC-DMD) method, to analyze the …