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Long short-term memory (LSTM)-based news classification model. [PDF]
PLoS ONEIn this study, we used unidirectional and bidirectional long short-term memory (LSTM) deep learning networks for Chinese news classification and characterized the effects of contextual information on text classification, achieving a high level of ...
Chen Liu
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Lane Position Detection Based on Long Short-Term Memory (LSTM) [PDF]
Sensors, 2020 Accurate detection of lane lines is of great significance for improving vehicle driving safety. In our previous research, by improving the horizontal and vertical density of the detection grid in the YOLO v3 (You Only Look Once, the 3th version) model ...
Wei Yang +5 more
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Intrusion detection systems using long short-term memory (LSTM) [PDF]
Journal of Big Data, 2021 An intrusion detection system (IDS) is a device or software application that monitors a network for malicious activity or policy violations. It scans a network or a system for a harmful activity or security breaching. IDS protects networks (Network-based
FatimaEzzahra Laghrissi +3 more
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Performance optimization for Intrusion Detection by Long Short Term Memory (LSTM) [PDF]
E3S Web of Conferences, 2023 Concerns about cyber threats have emerged as the expansion of system connectivity and the proliferation of system applications intensified in the industry.
Khatkar Monika +8 more
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Prediksi Harga Cryptocurrency Menggunakan Algoritma Long Short Term Memory (LSTM)
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 Technological developments continue to encourage the creation of various innovations in almost all aspects of human life. One of the innovations that is becoming a worldwide phenomenon today is the presence of cryptocurrency as a digital currency that ...
Moch Farryz Rizkilloh, Sri Widiyanesti
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Action Recognition Algorithm of Spatio–Temporal Differential LSTM Based on Feature Enhancement
Applied Sciences, 2021 The Long Short-Term Memory (LSTM) network is a classic action recognition method because of its ability to extract time information. Researchers proposed many hybrid algorithms based on LSTM for human action recognition. In this paper, an improved Spatio–
Kai Hu +4 more
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An improved LSTM-Seq2Seq-based forecasting method for electricity load
Frontiers in Energy Research, 2023 Power load forecasting has gained considerable research interest in recent years. The power load is vulnerable to randomness and uncertainty during power grid operations.
Yangyang Mu +4 more
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IEEE Access, 2022 In multivariate time series modeling, it is necessary to capture short-term mutation and long-term dependence information simultaneously. However, mechanism which can capture short-term change is difficult to be used to grasp long-term dependence ...
Shufang Feng, Yong Feng
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Complexity, 2023 Precise inventory prediction is the key to goods inventory and safety management. Accurate inventory prediction improves enterprises’ production efficiency. It is also essential to control costs and optimize the supply chain’s performance.
Tengfei Lei +4 more
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Improved LSTM Method of Predicting Cryptocurrency Price Using Short-Term Data
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2023 As cryptocurrencies develop, it cannot be denied that crypto prices are volatile. One of the influencing factors is the increasing volume of transactions which attracts the interest of researchers to conduct research in developing coin price predictions ...
Risna Sari +3 more
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