Semantic similarity dissociates shortfrom long-term recency effects: testing a neurocomputational model of list memory [PDF]
, 2006 The finding that recency effects can occur not only in immediate free recall (i.e., short-term recency) but also in the continuous-distractor task (i.e., long-term recency) has led many theorists to reject the distinction between short- and long-term ...
Usher, Marius +3 more
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Forecasting Nonadiabatic Dynamics using Hybrid Convolutional Neural Network/Long Short-Term Memory Network [PDF]
, 2021 Modeling nonadiabatic dynamics in complex molecular or condensed-phase systems has been challenging especially for the long-time dynamics. In this work, we propose a time series machine learning scheme based on the hybrid convolutional neural network ...
Jiebo, Li +3 more
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Phonological short term-memory, working memory and foreign language performance in intensive language learning. [PDF]
, 2008 In our research we addressed the question what the relationship is between phonological short-term and working memory capacity and performance in an end-of-year reading, writing, listening, speaking and use of English test.
Sáfár, Anna, Kormos, Judit
core +5 more sources
Non-Intrusive Load Identification Method Based on Improved Long Short Term Memory Network
Energies, 2021 Non-intrusive load monitoring (NILM) is an important research direction and development goal on the distribution side of smart grid, which can significantly improve the timeliness of demand side response and users’ awareness of load.
Jiateng Song +5 more
doaj +1 more source
Thermal error compensation method of truss robot beam structure based on mechanism and data drive
International Journal of Advanced Robotic Systems, 2023 As the main supporting component of the truss robot, the thermal deformation of the beam often has a great influence on the overall thermal error of the truss robot due to its large span.
Long Li +3 more
doaj +1 more source
Adaptive Clustering Long Short-Term Memory Network for Short-Term Power Load Forecasting
Energies, 2023 Short-term load forecasting (STLF) plays an important role in facilitating efficient and reliable operations of power systems and optimizing energy planning in the electricity market.
Yuanhang Qi +4 more
doaj +1 more source
Optimized Deep Stacked Long Short-Term Memory Network for Long-Term Load Forecasting
IEEE Access, 2021 Long-term load forecasting (LTLF) is an essential process for strategical planning of the future needed extension in the power systems of any country.
Tamer Ahmed Farrag, Ehab E. Elattar
doaj +1 more source
Long Short-Term Memory-Networks for Machine Reading [PDF]
Proceedings of the 2016 Conference on Empirical Methods in Natural
Language Processing, 2016 In this paper we address the question of how to render sequence-level networks better at handling structured input. We propose a machine reading simulator which processes text incrementally from left to right and performs shallow reasoning with memory and attention.
Cheng, Jianpeng +2 more
openaire +4 more sources
Sensors, 2022 Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units.
Lichao Sun +4 more
doaj +1 more source
Combined Long Short-Term Memory Network-Based Short-Term Prediction of Solar Irradiance
International Journal of Photoenergy, 2022 Achieving the highly accurate and generic prediction of solar irradiance is arduous because solar irradiance possesses intermittent randomness and is influenced by meteorological parameters.
Manoharan Madhiarasan, Mohamed Louzazni
doaj +1 more source