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Reservoir production capacity prediction of Zananor field based on LSTM neural network
This paper aims to explore the application of artificial intelligence in the petroleum industry, with a specific focus on oil well production...
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Speech emotion recognition based on Graph-LSTM neural network
Currently, Graph Neural Networks have been extended to the field of speech signal processing. It is the more compact and flexible way to represent...
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Hybrid LSTM-Graph Convolutional Neural Network with Wavelet Transform and Correlation Analysis for Electrical Demand Forecasting
Accurate electrical demand forecasting is essential for power system efficiency, renewable energy investment, and cost-effective electricity...
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Motion simulation of moorings using optimized LSTM neural network
Mooring arrays have been widely deployed in sustained ocean observation in high resolution to measure finer dynamic features of marine phenomena....
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RCLSTMNet: A Residual-convolutional-LSTM Neural Network for Forecasting Cutterhead Torque in Shield Machine
During tunneling process, it is of critical importance to dynamically adjust operation parameters of shield machine due to changes of geological...
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On the use of VMD-LSTM neural network for approximate earthquake prediction
Earthquake prediction has been widely studied in many fields using various technologies, including machine learning, which is able to explore the...
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High-speed railway seismic response prediction using CNN-LSTM hybrid neural network
In addressing the challenges of analyzing seismic response data for high-speed railroads, this research introduces a hybrid prediction model...
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An adsorption isotherm identification method based on CNN-LSTM neural network
ContextThe morphology of adsorption isotherms embodies a wealth of information regarding various adsorption mechanisms, rendering the classification...
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The prediction model of water level in front of the check gate of the LSTM neural network based on AIW-CLPSO
To solve the problem of predicting water level in front of check gate under different time scales, a different time scale prediction model with a...
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PM2.5 concentration prediction using weighted CEEMDAN and improved LSTM neural network
As the core of pollution prevention and management, accurate PM2.5 concentration prediction is crucial for human survival. However, due to the...
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Self-attention (SA) temporal convolutional network (SATCN)-long short-term memory neural network (SATCN-LSTM): an advanced python code for predicting groundwater level
Groundwater level prediction is important for effective water management. Accurately predicting groundwater levels allows decision-makers to make...
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Fake news detection using recurrent neural network based on bidirectional LSTM and GloVe
In the world of technology, the electronic and technical development of the fields of communication and the internet has increased, which has caused...
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Sensitivity analysis of regional rainfall-induced landslide based on UAV photogrammetry and LSTM neural network
Rainfall stands out as a critical trigger for landslides, particularly given the intense summer rainfall experienced in Zheduotang, a transitional...
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Enhancing efficiency and capacity of telehealth services with intelligent triage: a bidirectional LSTM neural network model employing character embedding
BackgroundThe widespread adoption of telehealth services necessitates accurate online department selection based on patient medical records, a task...
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Towards Efficient Recurrent Architectures: A Deep LSTM Neural Network Applied to Speech Enhancement and Recognition
Long short-term memory (LSTM) has proven effective in modeling sequential data. However, it may encounter challenges in accurately capturing...
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LSTM-based recurrent neural network provides effective short term flu forecasting
BackgroundInfluenza virus is responsible for a yearly epidemic in much of the world. To better predict short-term, seasonal variations in flu...
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Status Quo and Influence of Martial Arts Fitness in Pursuit of Health Using LSTM Recurrent Neural Network Algorithm
With the acceleration of the socialist modernization process, people’s living standards continue to improve, and the modernization of cities is also...
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Rotor Temperature Prediction of PMSM Based on LSTM Neural Networks
The rotor of the permanent magnet synchronous motor develops localized high temperatures at high-torque or high-speed operating conditions so that...
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Energy-based features and bi-LSTM neural network for EEG-based music and voice classification
The human brain receives stimuli in multiple ways; among them, audio constitutes an important source of relevant stimuli for the brain regarding...
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Using cutting temperature and chip characteristics with neural network BP and LSTM method to predicting tool life
The die steel NAK80 is used in specular optical molds, deep drawing forming dies, and cold extrusion dies in large quantities; high strength and...
