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Jointly Optimizing the IT and Cooling Systems for Data Center Energy Efficiency based on Multi-Agent Deep Reinforcement Learning., , , , , and . e-Energy, page 489-495. ACM, (2020)InjectTST: Injecting Global Information into Independent Channels for Long Time Series Forecasting., , , , , , , and . ICASSP, page 1-5. IEEE, (2025)Energy-aware Fault-tolerant Scheduling Scheme based on Intelligent Prediction Model for Cloud Data Center., , , and . IGSC, page 1-8. IEEE, (2018)An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction., , , , , and . ISCC, page 1-6. IEEE, (2020)A Deep Reinforcement Learning-based Task Scheduling Algorithm for Energy Efficiency in Data Centers., , , , , , , and . ICCCN, page 1-9. IEEE, (2021)An Energy-aware Virtual Machine Placement Algorithm in Cloud Data Center., , , , , and . ICIIP, page 1:1-1:9. ACM, (2017)A joint energy efficiency optimization scheme based on marginal cost and workload prediction in data centers., , , , , , and . Sustain. Comput. Informatics Syst., (2021)InjectTST: A Transformer Method of Injecting Global Information into Independent Channels for Long Time Series Forecasting., , , , , , , and . CoRR, (2024)JT-DA: Enhancing Data Analysis with Tool-Integrated Table Reasoning Large Language Models., , , , , , , , , and 2 other author(s). CoRR, (December 2025)Eco-friendly Dynamic Task Scheduling for Regional Data Center., , , , , and . e-Energy, page 566-571. ACM, (2020)