Research on Cloud Computing load forecasting based on LSTM-ARIMA combined model

Author:

Liu Xiaomin1,Xie Xiaolan1,Guo Qiang1

Affiliation:

1. Guilin University of Technology,Guangxi Key Laboratory of Embedded Technology and Intelligent System,Guilin,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Reference10 articles.

1. Univariate time series prediction of solar power using a hybrid wavelet-ARMA-NARX prediction method

2. Workload predic-tion using ARIMA statistical model and long short term memory recurrent neural networks[C];sudhakar;Proc of 2018 Inter-national Conference on Computing Power and Communica-tion Technologies (GUCON),2018

3. Determining objective weights in multiple criteria problems: The critic method

4. Adaptive regressive holt – winters workload prediction and firefly optimized lottery scheduling for load balancing in cloud [J];prassanna;Wireless Networks,2019

5. An ensemble of automatic algorithms for forecasting resource utilization in cloud

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Analysis of Clustering Effects In Cloud Workload Forecasting;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06

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