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PCP-2LSTM: Two Stacked LSTM-Based Prediction Model for Power Consumption in Data Centers., , , , , , and . CBD, page 13-18. IEEE, (2019)Multi-Granularity Power Prediction for Data Center Operations via Long Short-Term Memory Network., , , , and . ISPA/BDCloud/SocialCom/SustainCom, page 194-201. IEEE, (2019)Measuring Height Difference Using Two-Way Satellite Time and Frequency Transfer., , , , , and . Remote. Sens., 14 (3): 451 (2022)A Truthful FPTAS Auction for the Edge-Cloud Pricing Problem., , and . BigCom, page 140-144. IEEE, (2020)Unifying the Regional Height System Using Optic-Fiber Clock Network: A Simulation Test for Southeast Asia., , and . IEEE Access, (2023)Estimating Power Consumption of Containers and Virtual Machines in Data Centers., , , , and . CLUSTER, page 288-293. IEEE, (2020)DPAST-RNN: A Dual-Phase Attention-Based Recurrent Neural Network Using Spatiotemporal LSTMs for Time Series Prediction., , , , and . ICONIP (3), volume 12534 of Lecture Notes in Computer Science, page 568-578. Springer, (2020)Policy Learning for Balancing Short-Term and Long-Term Rewards., , , , , and . ICML, OpenReview.net, (2024)Data characteristics aware prediction model for power consumption of data center servers., , , , , and . Concurr. Comput. Pract. Exp., (2022)Measuring the gravity potential between two remote sites with CVSTT technique using two hydrogen clocks., , , , and . Geo spatial Inf. Sci., 27 (5): 1719-1738 (September 2024)