Integrated deep learning method for workload and resource prediction in cloud systems
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Title
Integrated deep learning method for workload and resource prediction in cloud systems
Authors
Keywords
Cloud data centers, BG-LSTM, Hybrid prediction, Savitzky–Golay filter, Deep learning
Journal
NEUROCOMPUTING
Volume 424, Issue -, Pages 35-48
Publisher
Elsevier BV
Online
2020-11-25
DOI
10.1016/j.neucom.2020.11.011
References
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- Host load prediction with long short-term memory in cloud computing
- (2017) Binbin Song et al. JOURNAL OF SUPERCOMPUTING
- Generating Highly Accurate Predictions for Missing QoS Data via Aggregating Nonnegative Latent Factor Models
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- A Forecasting Methodology for Workload Forecasting in Cloud Systems
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- Incremental Support Vector Learning for Ordinal Regression
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- (2014) Rongdong Hu et al. TheScientificWorldJOURNAL
- Multi-step-ahead time series prediction using multiple-output support vector regression
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- Iterated time series prediction with multiple support vector regression models
- (2012) Li Zhang et al. NEUROCOMPUTING
- Empirical prediction models for adaptive resource provisioning in the cloud
- (2011) Sadeka Islam et al. Future Generation Computer Systems-The International Journal of eScience
- Multiple-output modeling for multi-step-ahead time series forecasting
- (2010) Souhaib Ben Taieb et al. NEUROCOMPUTING
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