Results 31 to 40 of about 44,794 (286)

Short-term traffic flow prediction: An ensemble machine learning approach

Alexandria Engineering Journal, 2023
The inconvenience of travel, air pollution and consequent economic losses caused by traffic congestion have seriously restricted the healthy and sustainable development of cities in China.
Guowen Dai, Jinjun Tang, Wang Luo
doaj   +1 more source

Casimir energy and black hole pair creation in Schwarzschild-de Sitter spacetime [PDF]

, 2001
Following the subtraction procedure for manifolds with boundaries, we calculate by variational methods, the Schwarzschild-de Sitter and the de Sitter space energy difference.
Berger M, Bousso R, Bousso R, Bousso R, Bousso R, Bousso R, Bytsenko A, Coleman S, Cornwall J M, Demers J-G, Esposito G, Frolov V P, Frolov V P, Garattini R, Garattini R, Garattini R, Garattini R, Garattini R, Garattini R, Garattini R, Garattini R, Garattini R, Hawking S W, Hawking S W, Hawking S W, Hawking S W, Hawking S W, Maluf J W, Mann R B, Mann R B, Mann R B, Mann R B, Mann R B, Misner C W, Nariai S, Nariai S, Nojiri S, Nojiri S, Nojiri S, Nojiri S, Nojiri S, Prestidge T, Remo Garattini, Romeo A, Susskind L, Szekeres G, Volkov M S, Wu Z C, Wu Z C, Wu Z C, York J W Jr, York J W Jr   +51 more
core   +2 more sources

A novel few-sample wind power prediction model based on generative adversarial network and quadratic mode decomposition

Frontiers in Energy Research, 2023
With the emergence of various new power systems, accurate wind power prediction plays a critical role in their safety and stability. However, due to the historical wind power data with few samples, it is difficult to ensure the accuracy of power system ...
Hang He, Hang He, Manman Yuan
doaj   +1 more source

Reduced-order variational mode decomposition

, 2022
A novel data-driven method of modal analysis for complex flow dynamics, termed as reduced-order variational mode decomposition (RVMD), has been proposed, combining the idea of the separation of variables and a state-of-the-art nonstationary signal-processing technique -- variational mode decomposition.
Liao, Zi-Mo, Zhao, Zhiye, Chen, Liang-Bing, Wan, Zhen-Hua, Liu, Nan-Sheng, Lu, Xi-Yun   +5 more
openaire   +2 more sources

Harmonic Detection for Power Grids Using Adaptive Variational Mode Decomposition

Energies, 2019
The harmonic pollution problem in power grids has become increasingly prominent with the large-scale application of power electronic equipment, nonlinear loads, and renewable energy.
Guowei Cai, Lixin Wang, Deyou Yang, Zhenglong Sun, Bo Wang   +4 more
doaj   +1 more source

Kernel methods for detecting coherent structures in dynamical data

, 2019
We illustrate relationships between classical kernel-based dimensionality reduction techniques and eigendecompositions of empirical estimates of reproducing kernel Hilbert space (RKHS) operators associated with dynamical systems.
Husic, Brooke E., Klus, Stefan, Mollenhauer, Mattes, Noé, Frank   +3 more
core   +1 more source

A Study on Agricultural Commodity Price Prediction Model Based on Secondary Decomposition and Long Short-Term Memory Network

Agriculture, 2023
In order to address the significant prediction errors resulting from the substantial fluctuations in agricultural product prices and the non-linear features, this paper proposes a hybrid forecasting model based on variational mode decomposition (VMD ...
Changxia Sun, Menghao Pei, Bo Cao, Saihan Chang, Haiping Si   +4 more
doaj   +1 more source

Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data

, 2015
We present a Bayesian non-negative tensor factorization model for count-valued tensor data, and develop scalable inference algorithms (both batch and online) for dealing with massive tensors.
DB Dunson, EC Chi, G Heinrich, MD Hoffman, MI Jordan, O Cappé, TG Kolda   +6 more
core   +1 more source

Bayesian Robust Tensor Factorization for Incomplete Multiway Data [PDF]

, 2015
We propose a generative model for robust tensor factorization in the presence of both missing data and outliers. The objective is to explicitly infer the underlying low-CP-rank tensor capturing the global information and a sparse tensor capturing the ...
Amari, Shun-ichi, Cichocki, Andrzej, Zhang, Liqing, Zhao, Qibin, Zhou, Guoxu   +4 more
core   +1 more source

Localization and Pattern Formation in Quantum Physics. II. Waveletons in Quantum Ensembles

, 2005
In this second part we present a set of methods, analytical and numerical, which can describe behaviour in (non) equilibrium ensembles, both classical and quantum, especially in the complex systems, where the standard approaches cannot be applied.
Fedorova, Antonina N., Zeitlin, Michael G.   +1 more
core   +2 more sources