H-BILSTM: A Novel Bidirectional Long Short Term Memory Network Based Intelligent Early Warning Scheme in Mobile Edge Computing (MEC)
Author:
Affiliation:
1. School of Software, Xinjiang University, Urumqi, Xinjiang, China
2. School of Computer Science and Engineering, Central South University, changsha, Hunan, China
3. School of Mathematics, Hunan University, changsha, Hunan, China
Funder
New Generation Artificial Intelligence Project
Key Research and Development Program of Xinjiang Autonomous Region
National Key R&D Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Human-Computer Interaction,Information Systems,Computer Science (miscellaneous)
Link
http://xplorestaging.ieee.org/ielx7/6245516/10058698/09877956.pdf?arnumber=9877956
Reference38 articles.
1. High-Performance Time Series Prediction With Predictive Error Compensated Wavelet Neural Networks
2. Short-Term Traffic Flow Prediction for Urban Road Sections Based on Time Series Analysis and LSTM_BILSTM Method
3. Survey on Machine Learning for Intelligent End-to-End Communication Toward 6G: From Network Access, Routing to Traffic Control and Streaming Adaption
4. Predicting Blood Glucose with an LSTM and Bi-LSTM Based Deep Neural Network
5. An Intelligent Traffic Load Prediction-Based Adaptive Channel Assignment Algorithm in SDN-IoT: A Deep Learning Approach
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