Results 261 to 270 of about 10,612,437 (315)

A Dynamic Series Voltage Compensator for the Mitigation of LCC-HVDC Commutation Failure

IEEE Transactions on Power Delivery, 2021
To effectively mitigate the commutation failure (CF) of the line-commutated converter high-voltage direct current (LCC-HVDC) transmission system, a dynamic series voltage compensator (DSVC) scheme is proposed.
Lingxi Hou, Shuqing Zhang, Yingdong Wei, Biao Zhao, Qirong Jiang   +4 more
semanticscholar   +1 more source

Multiple Time Series Forecasting with Dynamic Graph Modeling

Proceedings of the VLDB Endowment, 2023
Multiple time series forecasting plays an essential role in many applications. Solutions based on graph neural network (GNN) that deliver state-of-the-art forecasting performance use the relation graph which can capture historical correlations among time
Kai Zhao, Chenjuan Guo, Yunyao Cheng, Peng Han, Miao Zhang, Bin Yang   +5 more
semanticscholar   +1 more source

Dynamic Seasonality in Time Series

SSRN Electronic Journal, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
So, Mike Ka Pui, Chung, Ray S. W.
openaire   +2 more sources

Dual-Dynamic-Bond Cross-Linked Antibacterial Adhesive Hydrogel Sealants with On-Demand Removability for Post-Wound-Closure and Infected Wound Healing.

ACS Nano, 2021
The design and development of a smart bioadhesive hydrogel sealant with self-healing and excellent antibacterial activity to achieve high wound closure effectiveness and post-wound-closure care is highly desirable in clinical applications.
Yuqing Liang, Zhenlong Li, Ying Huang, Rui Yu, Baolin Guo   +4 more
semanticscholar   +1 more source

Time Series and Dynamic Models

Journal of the American Statistical Association, 1998
Preface 1. Introduction Part I. Traditional Methods: 2. Linear regression for seasonal adjustment 3. Moving averages for seasonal adjustment 4. Exponential smoothing methods Part II. Probabilistic and Statistical Properties of Stationary Processes: 5. Some results on the univariate processes 6. The Box and Jenkins method for forecasting 7. Multivariate
Errol Caby, Christian Gourieroux, Alain Monfort   +2 more
openaire   +2 more sources

Random dynamical models from time series

Physical Review E, 2012
In this work we formulate a consistent Bayesian approach to modeling stochastic (random) dynamical systems by time series and implement it by means of artificial neural networks. The feasibility of this approach for both creating models adequately reproducing the observed stationary regime of system evolution, and predicting changes in qualitative ...
Y I, Molkov, E M, Loskutov, D N, Mukhin, A M, Feigin   +3 more
openaire   +2 more sources

Efficient Dynamic Latent Variable Analysis for High-Dimensional Time Series Data

IEEE Transactions on Industrial Informatics, 2020
Dynamic-inner canonical correlation analysis (DiCCA) extracts dynamic latent variables from high-dimensional time series data with a descending order of predictability in terms of $R^2$.
Yining Dong, Yingxiang Liu, S. J. Qin
semanticscholar   +1 more source

Molecular Dynamics Simulation of nCB series

AIP Conference Proceedings, 2007
This study describes the molecular dynamics (MD) simulations of the 4‐n‐alkyl‐4′‐cyanobiphenyl (nCB, n=5–9) liquid crystal homologous series at a selected temperature in the nematic phase. The order parameters and the biaxialities for five mesogens were found to be reasonable agreement with experiments.
Cebe, E., Capar, M. Ilk
openaire   +3 more sources