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Assessing Fairness of Residential Dynamic Pricing for Electricity using Active Learning with Agent-based Simulation.

, , , , и . AAMAS, стр. 1827-1836. International Foundation for Autonomous Agents and Multiagent Systems / ACM, (2024)

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Simulating residential Energy demand in Urban and Rural areas., , , , , и . WSC, стр. 548-559. IEEE, (2018)An Active Learning Method for the Comparison of Agent-based Models., , , , , , и . AAMAS, стр. 1377-1385. International Foundation for Autonomous Agents and Multiagent Systems, (2020)An Empirical Study of Flaky Tests in Android Apps., , и . ICSME, стр. 534-538. IEEE Computer Society, (2018)Modular and Extensible Pipelines for Residential Energy Demand Modeling and Simulation., , , , и . WSC, стр. 855-866. IEEE, (2022)Assessing Fairness of Residential Dynamic Pricing for Electricity using Active Learning with Agent-based Simulation., , , , и . AAMAS, стр. 1827-1836. International Foundation for Autonomous Agents and Multiagent Systems / ACM, (2024)A Network Synthesis and Analytics Pipeline with Applications to Sustainable Energy in Smart Grid., , , , и . e-Science, стр. 1-10. IEEE, (2023)OptICS-EV: A Data-Driven Model for Optimal Installation of Charging Stations for Electric Vehicles., , , , , и . ICCS (4), том 14076 из Lecture Notes in Computer Science, стр. 70-85. Springer, (2023)Budget-constrained optimal and equitable retrofitting problems for achieving energy efficiency., , и . e-Energy, стр. 473-484. ACM, (2023)A Reliability-aware Distributed Framework to Schedule Residential Charging of Electric Vehicles., , , , , и . IJCAI, стр. 5115-5121. ijcai.org, (2022)Fidelity and diversity metrics for validating hierarchical synthetic data: Application to residential energy demand., , , , и . IEEE Big Data, стр. 1377-1382. IEEE, (2022)