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A Long Short-Term Memory Neural Network
The neutrino oscillation probability depends heavily on the energy of the neutrino in question. However, we can not observe neutrinos directly, so an...
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Naive-LSTM based services awareness of edge computing elastic optical networks
Great challenges and demands are presented by increasing edge computing services for current elastic optical networks (EONs) to deal with serious...
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Determination of La in rare earth ores using laser-induced breakdown spectroscopy combined with bidirectional long short-term memory
The detection of lanthanum (La) is crucial for the extraction of rare earth minerals. As a real-time, in-situ detection technique, laser-induced...
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Dynamical prediction of two meteorological factors using the deep neural network and the long short-term memory (ΙΙ)
This paper presents the predictive accuracy using two-variate meteorological factors, average temperature and average humidity, in neural network...
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CSI-LSTM: a web server to predict protein secondary structure using bidirectional long short term memory and NMR chemical shifts
Protein secondary structure provides rich structural information, hence the description and understanding of protein structure relies heavily on it....
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A novel short-term radio flux trend prediction model based on deep learning
Solar radio flux is an important indicator of solar activity and solar UV burst. Accurate prediction of solar radio flux plays a crucial role in...
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Innovative use of optical sensors for real-time imaging and diagnosis using enhanced verge denoising and LSTM for sports medicine
In this article, researchers describe a novel method for identifying muscular tiredness in human subjects by combining surface electromyography...
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Application of long short-term memory neural network and optimal control to variable-order fractional model of HIV/AIDS
A variable-order fractional model of HIV/AIDS is proposed in this research. Afterward, the equilibrium points are determined, and their stability is...
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Prediction of ionospheric TEC by LSTM and OKSM during M class solar flares occurred during the year 2023
Advancements in space weather forecasting have become crucial for understanding and mitigating the impacts of solar activity on Earth’s ionosphere....
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Enhanced network lifespan in future wireless communication using machine learning based convolution neural networks
A collection of sensor nodes called a wireless sensor network is used to track and document the physical parameters of the surrounding area. The...
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Ionospheric TEC prediction using Long Short-Term Memory deep learning network
In this paper, the prediction model for ionospheric total electron content (TEC) based on Long Short-Term Memory (LSTM) deep learning network and its...
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Research on recognition of O-MI based on CNN combined with SST and LSTM
Recognition algorithms have been widely used in brain computer interface (BCI) for neural paradigms classification. To improve the classification and...
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Internal Leakage Diagnosis of a Hydraulic Cylinder Using C-LSTM Neural Network
The leakage in hydraulic cylinders is of utmost importance due to its critical nature and potential consequences like reduction in system efficiency...
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Forecasting the ionospheric F2 Parameters over Jeju Station (33.43°N, 126.30°E) by Using Long Short-Term Memory
Ionospheric models aim to simulate and predict variations in the ionosphere. In this study, we attempt to develop a regional ionospheric model to...
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Short-term forecast of high-energy electron flux based on GPR
The rapid enhancement of high-energy electron flux affects the safe operation of satellites in the synchronous orbit area, so accurate forecast of...
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A Long Short-Term Memory Neural Network Used to Predict the Exon–Intron Structure of a Gene
Several models of long short-term memory (LSTM) neural networks were constructed. Each model was trained on the complete mouse genome to predict the...
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Using Recurrent Neural Networks to Reconstruct Temperatures from Simulated Fluorescent Data for Use in Bio-microfluidics
Many biological systems have a narrow temperature range of operation, meaning high accuracy and spatial distribution level are needed to study these...
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An efficient epileptic seizure detection based on tunable Q-wavelet transform and DCVAE-stacked Bi-LSTM model using electroencephalogram
The recording and measurement of the electric events of the brain utilizing an electroencephalogram (EEG) has turned out to be a prominent equipment...
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Quantum optical techniques for quality data transmission process in cognitive networks
Due to the advancement of high definition, 5G technologies, the Internet of Things, and Artificial Intelligence, the demand for optical networks has...
