Results 91 to 100 of about 208,635 (216)

State-of-Charge Estimation of Lithium-Ion Batteries Based on the CNN-Bi-LSTM-AM Model Under Low-Temperature Environments

open access: yesSensors
Accurate state-of-charge (SOC) estimation is essential for lithium-ion battery management, especially under low temperatures where traditional methods suffer from noise sensitivity and nonlinear dynamics.
Ran Li   +3 more
doaj   +1 more source

LSTM-GWO performance evaluation with experiment 2.

open access: yes, 2022
LSTM-GWO performance evaluation with experiment 2.
Naglaa Fathy Hassan (13189914)   +2 more
core   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

open access: yesDeep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li   +4 more
wiley   +1 more source

Forecasting Sesame Price in Ethiopia Using Recurrent Neural Network Based Deep Learning Algorithms

open access: yesInternational Journal of Computational Intelligence Systems
Sesame is Ethiopia's second-most important crop after coffee, supporting farmer incomes and contributing to foreign exchange earnings. In 2018, it generated approximately 449 million USD, and in 2010, it accounted for 14% of global exports.
Yihun Tewachew   +3 more
doaj   +1 more source

Convolutional Bidirectional Long Short-Term Memory for Deception Detection With Acoustic Features

open access: yesIEEE Access, 2018
Despite the widespread use of multi-physiological parameters for deception detection, they have been severely restricted due to the high degree of cooperation in contacting-detection.
Yue Xie   +4 more
doaj   +1 more source

TAMNet: Temporal and adaptive‐frequency network with MixStyle for cross‐region oil and fluid production forecasting

open access: yesDeep Underground Science and Engineering, EarlyView.
This paper presents temporal and adaptive‐frequency network with MixStyle (TAMNet), a deep time‐series modeling framework for accurate and robust multi‐well oil productivity forecasting. TAMNet integrates transformer and long short‐term memory architectures to capture both short‐ and long‐term temporal dependencies, enhanced by a temporal gate unit ...
Chunxi Yang   +6 more
wiley   +1 more source

Dynamic Sign Language Recognition in Bahasa using MediaPipe, Long Short-Term Memory, and Convolutional Neural Network

open access: yesJournal of Information Systems Engineering and Business Intelligence
Background: Communication is important for everyone, including individuals with hearing and speech impairments. For this demographic, sign language is widely used as the primary medium of communication with others who share similar conditions or with ...
Ivana Valentina Lemmuela   +2 more
doaj   +1 more source

A Probabilistic Fractional Order Physics Informed Mamba Kolmogorov‐Arnold Network for State‐of‐Charge Estimation in Grid‐Connected Battery Energy Storage Systems

open access: yesEnergy Science &Engineering, EarlyView.
This paper introduces the probabilistic fractional‐order Mam‐KAN (PFO‐Mam‐KAN) controller, a physics‐informed gray‐box framework for real‐time battery state‐of‐charge estimation. By unifying efficient Mamba encoders with uncertainty‐aware fractional physics, it achieves superior 0.31% RMSE accuracy and robust grid‐support operation under dynamic ...
Arun Kumar Rawat   +2 more
wiley   +1 more source

The analysis of bidirectional long short-term memory network model for construction of cultural gene map and information extraction

open access: yesScientific Reports
To create a cultural gene map and extract information, this paper introduces a two-way long and short-term memory network (LSTM) model and verifies it using Jinxiu Yao headwear as an example.
Xing Ding, Jing Wang
doaj   +1 more source

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

open access: yesEnergy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani   +4 more
wiley   +1 more source

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