Results 31 to 40 of about 208,635 (216)

sungwookwi/Central-Valley-LSTM: v1.0.0

, 2022
<p>LSTM streamflow predictions for the Central Valley of California.</p ...
sungwookwi
core   +1 more source

A Hybrid GAS-ATT-LSTM Architecture for Predicting Non-Stationary Financial Time Series

Mathematics
This study proposes a hybrid approach to analyze and forecast non-stationary financial time series by combining statistical models with deep neural networks. A model is introduced that integrates three key components: the Generalized Autoregressive Score
Kevin Astudillo, Miguel Flores, Mateo Soliz, Guillermo Ferreira, José Varela-Aldás   +4 more
doaj   +1 more source

Sequential Modeling for the Recognition of Activities in Logistics

Sukkur IBA Journal of Emerging Technologies, 2021
Activity recognition is an important task in cyber physical system research and has been the focus of researchers worldwide. This paper presents a method for activity recognition in logistic operations using data from accelerometer and gyroscope sensors.
Zafi Sherhan Syed, Muhammad Zaigham Abbas Shah Syed, Muhammad Shehram Shah Syed, Aunsa Shah   +3 more
doaj   +1 more source

Bidirectional LSTM (Bi-LSTM) network.

, 2019
Bidirectional LSTM (Bi-LSTM) network.
Yinhai Wang (182679), Hao Yang (328526), Jianwei Wang (128689), Xin Fu (448766), Chenxi Liu (286325)   +4 more
core   +1 more source

Bidirectional Long Short-Term Memory Development for Aircraft Trajectory Prediction Applications to the UAS-S4 Ehécatl

Aerospace
The rapid advancement of unmanned aerial systems in various civilian roles necessitates improved safety measures during their operation. A key aspect of enhancing safety is effective collision avoidance, which is based on conflict detection and is ...
Seyed Mohammad Hashemi, Ruxandra Mihaela Botez, Georges Ghazi   +2 more
doaj   +1 more source

LSTM-based Multi-Step SOC Forecasting of Battery Energy Storage in Grid Ancillary Services

, 2021
Battery energy storage (BES) participation in the grid ancillary services markets is increasing rapidly in recent years. To facilitate optimal participation, the need for accurate BES state-of-charge (SOC) forecasting is indispensable.
Ardiansyah Ardiansyah (11241801), Yeonghyeon Kim (11241807), Deokjai Choi (11241815)   +2 more
core   +1 more source

Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series

Remote Sensing, 2022
The state of Amapá within the Amazon biome has a high complexity of ecosystems formed by forests, savannas, seasonally flooded vegetation, mangroves, and different land uses. The present research aimed to map the vegetation from the phenological behavior
Ivo Augusto Lopes Magalhães, Osmar Abílio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Anesmar Olino de Albuquerque, Potira Meirelles Hermuche, Éder Renato Merino, Roberto Arnaldo Trancoso Gomes, Renato Fontes Guimarães   +7 more
doaj   +1 more source

Detection of fake news using deep learning CNN–RNN based methods

ICT Express, 2022
Fake news is inaccurate information that is intentionally disseminated for a specific purpose. If allowed to spread, fake news can harm the political and social spheres, so several studies are conducted to detect fake news.
I. Kadek Sastrawan, I.P.A. Bayupati, Dewa Made Sri Arsa   +2 more
doaj   +1 more source

Incremental updates for efficient bidirectional transformations [PDF]

, 2011
A bidirectional transformation is a pair of mappings between source and view data objects, one in each direction. When the view is modified, the source is updated accordingly.
Wu, N, Wang, Meng,, Gibbons, J, Nicolas Wu, Wang, M, Gibbons, Jeremy, Wu, Nicolas, Meng Wang, Wang, Meng, Jeremy Gibbons, Gibbons, Jeremy,, Wu, Nicolas,   +11 more
core   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source