Cover Image

Dynamic Load Model for Data Centers with Pattern-Consistent Calibration

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lu, Siyu, Xiao, Chenhan, Weng, Yang
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Distribution Grid Line Outage Identification with Unknown Pattern and Performance Guarantee
by: Xiao, Chenhan, et al.
Published: (2023)

Limits of Residual-Based Detection for Physically Consistent False Data Injection
by: Xiao, Chenhan, et al.
Published: (2026)

External Data-Enhanced Meta-Representation for Adaptive Probabilistic Load Forecasting
by: Li, Haoran, et al.
Published: (2025)

PowerGrow: Feasible Co-Growth of Structures and Dynamics for Power Grid Synthesis
by: He, Xinyu, et al.
Published: (2025)

Generalizable Machine Learning Models for Predicting Data Center Server Power, Efficiency, and Throughput
by: Lei, Nuoa, et al.
Published: (2025)

Towards Intrinsically Calibrated Uncertainty Quantification in Industrial Data-Driven Models via Diffusion Sampler
by: Ma, Yiran, et al.
Published: (2026)

ExARNN: An Environment-Driven Adaptive RNN for Learning Non-Stationary Power Dynamics
by: Li, Haoran, et al.
Published: (2025)

Interpolation Conditions for Data Consistency and Prediction in Noisy Linear Systems
by: Vanelli, Martina, et al.
Published: (2025)

Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
by: Tao, Zhenyu, et al.
Published: (2024)

Smart Predict-then-Optimize Method with Dependent Data: Risk Bounds and Calibration of Autoregression
by: Liu, Jixian, et al.
Published: (2024)

Applying Fine-Tuned LLMs for Reducing Data Needs in Load Profile Analysis
by: Hu, Yi, et al.
Published: (2024)

Generative Design for Direct-to-Chip Liquid Cooling for Data Centers
by: Liu, Zheng
Published: (2026)

Learning Physically Consistent Lagrangian Control Models Without Acceleration Measurements
by: Laiche, Ibrahim, et al.
Published: (2025)

DCoPilot: Generative AI-Empowered Policy Adaptation for Dynamic Data Center Operations
by: Li, Minghao, et al.
Published: (2026)

SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning
by: Huang, Tzu-Yuan, et al.
Published: (2025)

DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
by: Guillen-Perez, Antonio, et al.
Published: (2025)

BuilDyn: Excitation-Driven Data Generation for Building Thermal Dynamics Modeling and Control
by: Koch, Felix, et al.
Published: (2026)

Resilient Load Forecasting under Climate Change: Adaptive Conditional Neural Processes for Few-Shot Extreme Load Forecasting
by: Hu, Chenxi, et al.
Published: (2026)

Exploring Lightweight Federated Learning for Distributed Load Forecasting
by: Duttagupta, Abhishek, et al.
Published: (2024)

A Configurable Pythonic Data Center Model for Sustainable Cooling and ML Integration
by: Naug, Avisek, et al.
Published: (2024)

Data Center Cooling System Optimization Using Offline Reinforcement Learning
by: Zhan, Xianyuan, et al.
Published: (2025)

Optimization-based Learning for Dynamic Load Planning in Trucking Service Networks
by: Ojha, Ritesh, et al.
Published: (2023)

Modeling IoT Traffic Patterns: Insights from a Statistical Analysis of an MTC Dataset
by: Ruiz-Guirola, David E., et al.
Published: (2024)

Learning Load Balancing with GNN in MPTCP-Enabled Heterogeneous Networks
by: Ji, Han, et al.
Published: (2024)

Task-Aware Machine Unlearning and Its Application in Load Forecasting
by: Xu, Wangkun, et al.
Published: (2023)

Process Knowledge Driven Change Point Detection for Automated Calibration of Discrete Event Simulation Models Using Machine Learning
by: Yildirim, Suleyman, et al.
Published: (2020)

Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
by: Achterhold, Jan, et al.
Published: (2021)

Adaptive Resource Allocation Optimization Using Large Language Models in Dynamic Wireless Environments
by: Noh, Hyeonho, et al.
Published: (2025)

A Transition System Abstraction Framework for Neural Network Dynamical System Models
by: Yang, Yejiang, et al.
Published: (2024)

Learning Dynamical Systems by Leveraging Data from Similar Systems
by: Xin, Lei, et al.
Published: (2023)

Efficient and Robust Freeway Traffic Speed Estimation under Oblique Grid using Vehicle Trajectory Data
by: He, Yang, et al.
Published: (2024)

System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models
by: Li, Xiao, et al.
Published: (2023)

Sigma-point Kalman Filter with Nonlinear Unknown Input Estimation via Optimization and Data-driven Approach for Dynamic Systems
by: Loo, Junn Yong, et al.
Published: (2023)

Domain Consistent Industrial Decarbonisation of Global Coal Power Plants
by: Ashraf, Waqar Muhammad, et al.
Published: (2025)

Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes
by: Ewering, Jan-Hendrik, et al.
Published: (2025)

Enhancing Non-Intrusive Load Monitoring with Features Extracted by Independent Component Analysis
by: Hoosh, Sahar Moghimian, et al.
Published: (2025)

Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency
by: Zhou, Yuqi, et al.
Published: (2024)

HOPS: High-order Polynomials with Self-supervised Dimension Reduction for Load Forecasting
by: Song, Pengyang, et al.
Published: (2025)

SustainDC: Benchmarking for Sustainable Data Center Control
by: Naug, Avisek, et al.
Published: (2024)

Automated and Risk-Aware Engine Control Calibration Using Constrained Bayesian Optimization
by: Vlaswinkel, Maarten, et al.
Published: (2025)