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Non-linear Time Series Prediction using Improved CEEMDAN, SVD and LSTM
This study recommends a new time series forecasting model, namely ICEEMDAN - SVD - LSTM model, which coalesces Improved Complete Ensemble EMD with...
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ADLNet: an adaptive network for arrhythmia classification based on deformable convolution and LSTM
Detecting arrhythmia through electrocardiogram (ECG) signals is a challenging task, and some methods based on deep neural networks have been proposed...
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High-emitter identification for heavy-duty vehicles by temporal optimization LSTM and an adaptive dynamic threshold
Heavy-duty diesel vehicles are important sources of urban nitrogen oxides (NO x ) in actual applications for environmental compliance, emitting more...
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Intrusion detection in internet of things using improved binary golden jackal optimization algorithm and LSTM
Internet of things (IoT) technology has gained a reputation in recent years due to its ease of use and adaptability. Due to the amount of sensitive...
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An efficient proactive VM consolidation technique with improved LSTM network in a cloud environment
The power consumption of datacenters is multiplying, and several survey reports stated that the power consumption of datacenters will reach...
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Speech refinement using Bi-LSTM and improved spectral clustering in speaker diarization
In this digitally-driven culture, the need and demand for diarizing online meetings, classes, conferences, and medical diagnoses have increased a...
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Road pothole detection from smartphone sensor data using improved LSTM
Road abnormalities can be caused by man-made and natural disasters that affect the safety of drivers and damage vehicles. Therefore, several...
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Corrector LSTM: built-in training data correction for improved time-series forecasting
Traditional recurrent neural networks (RNNs) are essential for processing time-series data. However, they function as read-only models, lacking the...
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LSTM-based adaptive whale optimization model for classification of fused multimodality medical image
Multimodality medical image fusion is the important area in the medical imaging field which enhances the reliability of medical diagnosis. Medical...
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Enhancing patent text classification with Bi-LSTM technique and alpine skiing optimization for improved diagnostic accuracy
Currently, technological innovation has been increasingly valued by companies around the world, and patents as an important recording medium of...
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Deep adaptive CHIONet: designing novel herd immunity prediction of COVID-19 pandemic using hybrid RNN with LSTM
The rapid spread of COVID-19 threatened the entire world because of its adverse effects and high mortality rate. The most effective method of disease...
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Behavior recognition based on the improved density clustering and context-guided Bi-LSTM model
Context information is vital to research video human behavior recognition. Under the LSTM together with CNN of the framework, a novel action...
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Adaptive feature selection with deep learning MBi-LSTM model based paddy plant leaf disease classification
For some nations, including India, agriculture is the main source of income. Crop/plant infections are important factors in reduced production...
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An Improved Conv-LSTM Method for Gear Fault Detection
Reducing the occurrence of gear failures and extending their service life is a vital issue in industrial production. To solve the problem that the...
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ConvST-LSTM-Net: convolutional spatiotemporal LSTM networks for skeleton-based human action recognition
Human action recognition (HAR) emphases on perceiving and identifying the action behavior done by humans within an image/video. The HAR activities...
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Short-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)
Accurate sector-based air traffic flow predictions are essential for ensuring the safety and efficiency of the air traffic management (ATM) system....
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DyGCN-LSTM: A dynamic GCN-LSTM based encoder-decoder framework for multistep traffic prediction
Intelligent transportation systems (ITS) are gaining attraction in large cities for better traffic management. Traffic forecasting is an important...
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Enhanced cloud security: a novel intrusion detection system using ARSO algorithm and Bi-LSTM classifier
The cloud computing environment faces significant security challenges, impacting its long-term growth. Intrusion detection is crucial for mitigating...
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Mechanical element’s remaining useful life prediction using a hybrid approach of CNN and LSTM
For the safety and reliability of the system, Remaining Useful Life (RUL) prediction is considered in many industries. The traditional machine...
