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02/27/2023
Predicting the Performance of a Computing System with Deep Networks
Predicting the performance and energy consumption of computing hardware ...
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09/14/2022
Analysis of Reinforcement Learning for determining task replication in workflows
Executing workflows on volunteer computing resources where individual ta...
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07/11/2022
Long-term Reproducibility for Neural Architecture Search
It is a sad reflection of modern academia that code is often ignored aft...
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06/05/2022
Machine learning applications for electricity market agent-based models: A systematic literature review
The electricity market has a vital role to play in the decarbonisation o...
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09/10/2021
Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning
A lowering in the cost of batteries and solar PV systems has led to a hi...
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03/07/2021
The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets
Electricity supply must be matched with demand at all times. This helps ...
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11/08/2020
Exploring market power using deep reinforcement learning for intelligent bidding strategies
Decentralized electricity markets are often dominated by a small set of ...
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05/28/2020
Optimizing carbon tax for decentralized electricity markets using an agent-based model
Averting the effects of anthropogenic climate change requires a transiti...
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05/17/2020
Long-term electricity market agent based model validation using genetic algorithm based optimization
Electricity market modelling is often used by governments, industry and ...
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10/22/2019
ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning
Due to the threat of climate change, a transition from a fossil-fuel bas...
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10/06/2019
Optimising energy and overhead for large parameter space simulations
Many systems require optimisation over multiple objectives, where object...
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10/19/2018