Results 61 to 70 of about 1,862 (208)
A decomposition clustering ensemble learning approach for forecasting foreign exchange rates
A decomposition clustering ensemble (DCE) learning approach is proposed for forecasting foreign exchange rates by integrating the variational mode decomposition (VMD), the self-organizing map (SOM) network, and the kernel extreme learning machine (KELM).
Yunjie Wei +4 more
doaj +1 more source
An “Interface Reactor” strategy boosts simulation stability by 2–3 orders of magnitude, enabling stable 100 ns molecular dynamics of electrode‐electrolyte interfaces. Distinct SEI formation mechanisms are revealed: mixed co‐formation in carbonates versus surface‐energy‐controlled NaF crystallization in ethers. Metadynamics simulations further elucidate
Zhoulin Liu +6 more
wiley +1 more source
A weakly solvating ether solvent, 1,2‐dimethoxypropane (DMP), is proposed for use in localized high‐concentration electrolytes (LHCEs) for lithium metal batteries (LMBs). These DMP‐based LHCEs simultaneously suppress lithium metal corrosion and cathode degradation—two interrelated processes that accelerate calendar aging of LMBs.
Jisub Kim +14 more
wiley +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Bird Call Identification Using Ensemble Empirical Mode Decomposition
Birds are iconic species of the environment. Bird monitoring can be achieved by collecting recordings of the calls of wild birds and later identifying the species. A new approach suggested in this study involves the application of ensemble empirical mode
Jingxuan Liu, Hailan Chen
doaj +1 more source
Quantification of Dynamic Properties of Pile Using Ensemble Empirical Mode Decomposition
This paper investigated dynamical interactions between pile and frozen ground by using the ensemble empirical mode decomposition (EEMD) method. Unlike the conventional empirical mode decomposition (EMD) method, EEMD is found to be able to separate the ...
Feng Xiao +3 more
doaj +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
Low-coherence interferometry (LCI) has proved to be a useful tool in optical measurement and detection. However, the noise that is present in practical applications makes interference term retrieval (ITR) difficult.
Hongxia Zhang +4 more
doaj +1 more source
This paper proposes a framework combining the complementary ensemble empirical mode decomposition with both the independent component analysis and the non-negative matrix factorization for estimating both the heart rate and the respiratory rate from the ...
Ruisheng Lei +3 more
doaj +1 more source
Composite cathode degradation is not merely the sum of its particles. Kinetically mismatched populations develop state‐of‐charge differences that drive spontaneous internal Li‐ion transfer; the accompanying transient currents accelerate surface degradation.
Seheon Oh +5 more
wiley +1 more source

