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Dog behaviors identification model using ensemble convolutional neural long short-term memory networks
This paper presents a new model based on Convolutional Neural Networks (CNN) with a long short-term memory network (LSTM) and ensemble technique for...
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Short-Term Load Forecasting for Commercial Building Using Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) Network with Similar Day Selection Model
Load forecasting is essential in power systems for reliable and efficient energy planning and operation. Commercial buildings usually account for 20%...
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Real-Time Power System Transient Stability Prediction Using Convolutional Layer and Long Short-Term Memory
This paper proposes a real-time transient stability prediction model based on neural networks. The proposed convolutional long short-term memory...
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Long-term and short-term memory networks based on forgetting memristors
The hardware circuit of neural network based on forgetting memristors not only has the characteristics of high computational efficiency and low power...
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Vertical Wind Profile Estimation Using Hybrid Convolutional Neural Networks and Bidirectional Long Short-Term Memory
Determining the potential for develo** a wind farm requires accurate knowledge of the vertical profile of wind speed (WS) at present and in the...
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A deep learning approach for diagnosis of schizophrenia disorder via data augmentation based on convolutional neural network and long short-term memory
Schizophrenia (SZ) is a severe, chronic mental disorder without specific treatment. Due to the increasing prevalence of SZ in societies and the...
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State of Charge Estimation of Lithium-Ion Batteries Using Long Short-Term Memory and Bi-directional Long Short-Term Memory Neural Networks
This research proposes a data-driven method for estimating the state of charge of lithium-ion batteries using two neural networks, namely long...
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Develo** a Novel Long Short-Term Memory Networks with Seasonal Wavelet Transform for Long-Term Wind Power Output Forecasting
Long-term wind power forecasting is a challenging endeavor that requires predictions that span years into the future. Accurate forecasting is crucial...
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Minimum Noise Fraction and Long Short-Term Memory Model for Hyperspectral Imaging
In recent years, deep learning techniques have presented a major role in hyperspectral image (HSI) classification. Most commonly Convolutional Neural...
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Federated quantum long short-term memory (FedQLSTM)
Quantum federated learning (QFL) can facilitate collaborative learning across multiple clients using quantum machine learning (QML) models, while...
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Convolution Neural Network Bidirectional Long Short-Term Memory for Heartbeat Arrhythmia Classification
Arrhythmia is a heart condition that poses a severe threat to life and requires prompt medical attention. One of the challenges in detecting...
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Gesture Recognition of Filipino Sign Language Using Convolutional and Long-Short Term Memory Neural Network
Sign language is a form of communication prominently used by the deaf-mute community to convey their ideas and thoughts. In the Philippines, local...
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Emotion Recognition Using Ultra-Short-Term ECG Signals with a Hybrid Convolutional Neural Network and Long Short-Term Memory Network
This research aims to investigate emotion recognition using ultra-short-term electrocardiogram (ECG) signals with a hybrid convolutional neural...
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Convolutional Long Short-Term Memory Network Model for Dynamic Texture Classification: A Case Study
The digital world is witnessing the rapid growth of various data such as multimedia content. This enormous volume of information resources is...
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A Convolutional Neural Network Incorporated Long Short-Term Memory with Autoencoder for Covid-19 Intensity Levels Detection
The intelligent machine assisted diagnostics for the reliable and rapid identification of coronavirus disease (COVID-19) has become a most demanded...
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Deep learning framework for stock price prediction using long short-term memory
Forecasting stock prices is always considered as complicated process due to the dynamic and noisy characteristics of stock data influenced by...
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Bridge Structural Damage Identification Based on Parallel Multi-head Self-attention Mechanism and Bidirectional Long and Short-term Memory Network
To address the health monitoring challenges of bridge structures and identify suitable damage features, this paper initially denoises the input data...
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Indian Stock Price Prediction Using Long Short-Term Memory
In recent years, numerous researchers across the world have developed various methods for predicting stock prices. However, the accuracy of these...
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A Novel Video Prediction Algorithm Based on Robust Spatiotemporal Convolutional Long Short-Term Memory (Robust-ST-ConvLSTM)
Recently, video prediction algorithms based on neural networks have become a promising research direction. Therefore, a new recurrent video...
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Maintenance Prediction Based on Long Short-Term Memory Algorithm
Predictive maintenance is a prominent strategy that plays a key role in reducing the maintenance costs in manufacturing systems. It allows minimizing...