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Bi-directional Long Short Term Memory Neural Network for Short-Term Traffic Speed Prediction Using Gravitational Search Algorithm
Traffic speed prediction has implications for urban planning, congestion reduction, and intelligent control systems. To maintain a uniform traffic...
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Accuracy Improvement of Network Intrusion Detection System Using Bidirectional Long-Short Term Memory (Bi-LSTM)
An intrusion detection system (IDS), sometimes known as an infiltration prevention system, is an active defensive mechanism deployed by the Internet...
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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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Air Pollution Prediction Using Long Short-Term Memory Variants
Air pollution is an unresolved environmental problem that poses a health threat in many countries. Nearly 90% of the global population is exposed to...
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Tool wear prediction method based on bidirectional long short-term memory neural network of single crystal silicon micro-grinding
Although many efforts have been made on off-line tool wear prediction, the on-line intelligent prediction of tool wear prediction based on...
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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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Parts-of-Speech Tagger in Assamese Using LSTM and Bi-LSTM
Parts-of-speech (POS) tagging is considered one of the most challenging fields in natural language processing (NLP). The objective of this research...
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Cloud Computing Load Forecasting by Using Bidirectional Long Short-Term Memory Neural Network
Cloud services play an increasingly significant role in daily life. The widespread integration of the Internet of Things, and online services has...
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Two layered gated recurrent stacked long short-term memory networks for driver’s behavior analysis
In this work, an in-vehicle deep learning-based driver assistance system is proposed to monitor driver behavior to reduce the risk of road traffic...
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Fault classification of three phase induction motors using Bi-LSTM networks
The induction motors are back bone of the modern industry and play very important role in manufacturing and transportation sectors. The induction...
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Bi-RNN and Bi-LSTM Based Text Classification for Amazon Reviews
Electronic Commerce (E-Commerce) enables the effective implementation of product-based online business transactions. In this paper, we categorize the...
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Document-Level Chemical-Induced Disease Semantic Relation Extraction Using Bidirectional Long Short-Term Memory on Dependency Graph
Identifying chemical-induced disease (CID) semantic relations in the biomedical literature, including both intra- and inter-sentence interactions,...
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Subject-Wise Cognitive Load Detection Using Time–Frequency EEG and Bi-LSTM
Cognitive load detection using electroencephalogram (EEG) signals is a technique employed to understand and measure the mental workload or cognitive...
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Deep Bi-LSTM Neural Network for Short-Term Traffic Flow Prediction Under Heterogeneous Traffic Conditions
Continuous expansion of cities has resulted in the growing traffic network to cater the demand of increasing number of vehicles. The rapid growth in...
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ECG Signal Classification Using Long Short-Term Memory Neural Networks
This study proposes a neural-based approach to classify ECG signals acquired from a low-cost wearable device as an early warning system for possible...
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Electricity Theft Detection System for Smart Metering Application Using Bi-LSTM
Power theft is big issues in the field of electricity because it harms transmission lines and results in financial losses. So, it is important to...
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An effective hybrid optimal deep learning approach using BI-LSTM and restricted Boltzmann machines whale optimization to detect arrhythmia
Electrocardiography (ECG) is a widely recognized noninvasive method employed in the field of medical science to gather data pertaining to the cardiac...
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A seismic response prediction method based on a self-optimized Bayesian Bi-LSTM mixed network for high-speed railway track-bridge system
The construction of China’s high-speed railway (HSR) network has reached earthquake-prone regions, necessitating a timely and accurate post-disaster...
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Bi-directional LSTM for Monitoring Biceps Brachii Muscle Activity of Healthy Subjects Using sEMG Signals
In recent decades, EMG (Electromyogram) pattern recognition systems focus primarily on feature engineering techniques. Recently, feature learning has...
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A Defect Data Compensation Model for Infrared Thermal Imaging Based on Bi-LSTM with Attention Mechanism
The infrared thermal imager presents unique advantages in plate fault detection and prediction. However, during the data collection process, three...
