Results 81 to 90 of about 5,625,691 (189)

A Moving-Horizon Dynamic Mode Decomposition Method for Daily Residential Electric Consumption Prediction

IEEE Access
In this paper, a data-driven method is proposed for the prediction of daily residential electric consumption. The proposed method is based on the dynamic mode decomposition (DMD) approach and the moving-horizon principle, resulting in the so-called ...
Dinh Hoa Nguyen
doaj   +1 more source

Note on the Use of Dynamic Mode Decomposition in Mechanics

, 2023
We advocate for the use of Dynamic Mode Decomposition (DMD) in mechanics. Snapshots of the temperature or displacement fields are obtained; and the DMD algorithm, which, remarkably, requires a few lines of code, is applied to matrices obtained by time ...
Simha, Hari Manoj, Biglarbegian, M
core   +1 more source

Detection of Ship Wakes in Dynamic Sea Surface Video Sequences: A Data-Driven Approach

Remote Sensing
In order to enhance the detection of maritime vessel targets, considering the causal relationship between the motion of vessels and their wakes, as well as the characteristics of ship wakes such as large diffusion range and distinctive features, this ...
Chengcheng Yu, Yanmei Zhang, Meifang Xiao, Zhibo Zhang   +3 more
doaj   +1 more source

Dynamic Mode Decomposition with Non-uniform Sampling [PDF]

Dynamic Mode Decomposition (DMD) and its extensions (EDMD) have been at the forefront of data-based approaches to Koopman operators. Most (E)DMD algorithms assume that the entire state is sampled at a uniform sampling rate.
Anantharaman, Ramachandran, Mauroy, Alexandre   +1 more
core   +1 more source

A Fault Diagnosis Method for One-Dimensional Vibration Signal Based on Multiresolution tlsDMD and Approximate Entropy

Shock and Vibration, 2019
Dynamic mode decomposition (DMD) has certain advantages compared with the traditional fault signal diagnosis method. By exploiting the strength of DMD algorithm in signal processing, this paper proposes a joint fault diagnosis scheme to extract the ...
Zhang Dang, Yong Lv, Yourong Li, Guoqian Wei   +3 more
doaj   +1 more source

Latent Diffeomorphic Dynamic Mode Decomposition

We present Latent Diffeomorphic Dynamic Mode Decomposition (LDDMD), a new data reduction approach for the analysis of non-linear systems that combines the interpretability of Dynamic Mode Decomposition (DMD) with the predictive power of Recurrent Neural ...
Bertozzi, Andrea L, Schwenk, Jon, Diepeveen, Willem   +2 more
core   +1 more source

Clarifying the effect of mean subtraction on Dynamic Mode Decomposition [PDF]

Any autonomous nonlinear dynamical system can be viewed as a superposition of infinitely many linear processes, through the so-called Koopman mode decomposition.
Arbabi, Hassan, Mezić, Igor, Korda, Milan, Seenivasaharagavan, Gowtham S   +3 more
core   +1 more source

Dynamic Mode Decomposition via Polynomial Root-Finding Methods

Mathematics
Dynamic mode decomposition (DMD) is a powerful data-driven tool for analyzing complex systems that has gained significant attention in various scientific and engineering disciplines.
Gyurhan Nedzhibov
doaj   +1 more source

Tensor-based dynamic mode decomposition

, 2016
Dynamic mode decomposition (DMD) is a recently developed tool for the analysis of the behavior of complex dynamical systems. In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially high-dimensional ...
Klus, S., Schütte, Ch., Gelß, P., Peitz, S.   +3 more
core  

Coherent structures detection using the DMD and OPD methods: Differences between the methods and sensitivity to the adjustable parameters [PDF]

EPJ Web of Conferences
The turbulent part of the flow within the Atmospheric boundary layer is not necessarily totally random, but it usually reports some structures with inner coherence.
Kluková Zuzana, Nosek Štěpán, Jaňour Zbyněk   +2 more
doaj   +1 more source