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Forecasting time series accurately is critical to ensure the safety and reliability of complex system. So, time series prediction has been a popular subject. Normally, the information used in time series prediction is always mined from multi-variable time series and small simple data. Thus, based on grey prediction theory, an adaptive prediction model with multi-variable small simple time series data...
On-demand resource provisioning is with great challenge in cloud systems. The key problem is how to learn about the future workload in advance to help determine resource allocation. There are various prediction models developed to predict the future workload. The major problem of previous researches is that they assume that application workload has static pattern. In practice, so many application...
Thermal issues have become critical roadblocks for the development of advanced chip-multiprocessors (CMPs). In this paper, we introduce a new angle to view transient thermal analysis - based on predicting thermal profile, instead of calculating it. We develop a systematic framework that can learn different thermal profiles of a CMP by using an autoregressive (AR) model. The proposed AR model can serve...
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