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发表刊物：Neurocomputing
刊物所在地：荷兰
关键字：Cloud data centers, BG-LSTM, Hybrid prediction, Savitzky–Golay filter, Deep learning
摘要：Cloud computing providers face several challenges in precisely forecasting large-scale workload and resource time series. Such prediction can help them to achieve intelligent resource allocation for guaranteeing that users’ performance needs are strictly met with no waste of computing, network and storage resources. This work applies a logarithmic operation to reduce the standard deviation before smoothing workload and resource sequences. Then, noise interference and extreme points are removed via a powerful filter. A Min–Max scaler is adopted to standardize the data. An integrated method of d
论文类型：基础研究
论文编号：DOI: 10.1016/j.neucom.2020.11.011
一级学科：计算机科学与技术
文献类型：期刊
卷号：424
页面范围：35-48
ISSN号：0925-2312
是否译文：否
CN号：null
发表时间：2021-02-01
收录刊物：SCI
发布期刊链接：https://www-sciencedirect-com-s.vpn.buaa.edu.cn:8118/science/article/pii/S0925231220317884