Results 31 to 40 of about 3,768 (183)

Forecasting Cryptocurrency Prices Using LSTM, GRU, and Bi-Directional LSTM: A Deep Learning Approach

Fractal and Fractional, 2023
Highly accurate cryptocurrency price predictions are of paramount interest to investors and researchers. However, owing to the nonlinearity of the cryptocurrency market, it is difficult to assess the distinct nature of time-series data, resulting in ...
Phumudzo Lloyd Seabe, Claude Rodrigue Bambe Moutsinga, Edson Pindza   +2 more
doaj   +1 more source

Research of Attention-Based Bi-GRU-CRF for Slot Filling

Journal of Physics: Conference Series, 2021
Abstract Slot Filling (SF) is a critical part of spoken language understanding (SLU) which targets to capture semantic constituents from a specific utterance. It is considered as a sequence labeling issue. Currently, recurrent neural networks have shown promising effectiveness in this issue.
Luwang Zhou, Zhimin Huang, Ying Nie
openaire   +1 more source

Oilseed Rape Sclerotinia in Hyperspectral Images Segmentation Method Based on Bi-GRU and Spatial-Spectral Information Fusion

智慧农业
ObjectiveThe widespread prevalence of sclerotinia disease poses a significant challenge to the cultivation and supply of oilseed rape, not only results in substantial yield losses and decreased oil content in infected plant seeds but also severely ...
ZHANG Jing, ZHAO Zexuan, ZHAO Yanru, BU Hongchao, WU Xingyu   +4 more
doaj   +1 more source

Bi-GRU Based Deception Detection using EEG Signals

CoRR
Deception detection is a significant challenge in fields such as security, psychology, and forensics. This study presents a deep learning approach for classifying deceptive and truthful behavior using ElectroEncephaloGram (EEG) signals from the Bag-of-Lies dataset, a multimodal corpus designed for naturalistic, casual deception scenarios.
Danilo Avola, Muhammad Yasir Bilal, Emad Emam, Cristina Lakasz, Daniele Pannone, Amedeo Ranaldi   +5 more
openaire   +2 more sources

A Multi-Head Attention ResCNN–BiGRU Model for Robust SOC Estimation in EVs Lithium-Ion Batteries Using Real-World Driving Data

IEEE Access
Precise assessment of the state of charge (SOC) is essential for ensuring the safety, efficiency, and dependability of electric vehicles (EVs). However, achieving high accuracy remains challenging due to the complex nonlinear characteristics of lithium ...
N. Vigneswar, R. Manivannan, Chala Merga Abdissa   +2 more
doaj   +1 more source

Snow Depth Retrieval Using Detrended SNR From GNSS-R With Bidirectional GRU

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Snow depth monitoring is crucial for hydrology, climate research, and avalanche prediction. While traditional global navigation satellite system (GNSS) reflectometer methods offer cost-effective snow thickness retrieval, they suffer from poor accuracy ...
Wei Liu, Zihui Lin, Yuan Hu, Aodong Tian, Xintai Yuan, Jens Wickert   +5 more
doaj   +1 more source

A Partially Amended Hybrid Bi-GRU—ARIMA Model (PAHM) for Predicting Solar Irradiance in Short and Very-Short Terms

Energies, 2020
Solar renewable energy (SRE) applications are substantial in eradicating the rising global energy shortages and reversing the approaching environmental apocalypse.
Mustafa Jaihuni, Jayanta Kumar Basak, Fawad Khan, Frank Gyan Okyere, Elanchezhian Arulmozhi, Anil Bhujel, Jihoon Park, Lee Deog Hyun, Hyeon Tae Kim   +8 more
doaj   +1 more source

Photothermal CO2 Hydrogenation: Reactions, Mechanisms, and Catalyst Design

Carbon Energy, EarlyView.
Reactions, mechanisms, and catalyst design for photothermal CO2 hydrogenation. ABSTRACT Photothermal CO2 hydrogenation has attracted extensive attention because it provides a green and sustainable approach to fuel and chemicals production. The photothermal catalyst plays a critical role in CO2 conversion through a range of reactions.
Shuai Yan, Yuting Wang, Wenhao Zhao, Jinqiang Zhang, Guangyao Chen, Lei Jiang, Yun Wang, Yingquan Chen, Xiong Zhang, Xianhua Wang, Kuo Zeng, Hongqi Sun, Shuxin Ouyang, Yonggang Yao, Haiping Yang, Hanping Chen   +15 more
wiley   +1 more source

Landslide Displacement Prediction Based on Transfer Learning and Bi-GRU

Journal of Sensors, 2022
Predicting slope deformation prediction is crucial for early warning of slope failure, preventing damage to properties, and saving human lives. However, in practice, equipment maintenance causes discontinuity in the displacement data, and the traditional prediction models based on deep networks do not perform well in this case.
Haiqing Zheng, Mengfan Duan, Xiaoyun Sun, Guang Han, Qiang Jin   +4 more
openaire   +1 more source

Research on explainable BiGRU deep learning framework for short term load forecasting in smart power systems

Discover Artificial Intelligence
This study proposes a novel forecasting framework based on a parallel multi-input Bi-GRU architecture combined with a sliding window-based Multi-Input Multi-Output (MIMO) prediction strategy.
Zhiwei Wang, Mengzhou Xu, Jingchang Hao, Wei Li, Shiyao Cheng   +4 more
doaj   +1 more source