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Aug 20, 2026 -
Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Markdown Text - 738 B -
MD5: 99dac3f6c8b4464ca698e66431bfa302
Readme |
Aug 20, 2026 -
Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Tabular Data - 7.7 MB - 32 Variables, 8760 Observations - UNF:6:yVOI7v3nxbWQJc7oj81xpQ==
Weather data for Singapore |
Aug 20, 2026 -
Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Fixed Field Text Data - 123.9 MB -
MD5: 7cd2b57371973cec17482efe4baa38af
Approximate consumer models using simulation data |
Aug 20, 2026 -
Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Fixed Field Text Data - 310.9 MB -
MD5: 82fd6c3d135cd8fc988d120f3d9dfa80
Actual models used for evaluation |
Aug 20, 2026 -
Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Fixed Field Text Data - 78.2 MB -
MD5: 02ceb3e8dd7e1778575a6ce9f5e2f2c9
Actual models with override behaviour based on Sarran et al 2024 |
Aug 20, 2026 -
Replication Data for: Deep reinforcement learning for coordinated air-conditioner control in groups of buildings using smart meter data
Fixed Field Text Data - 310.9 MB -
MD5: 83fc5920cc453ffa08e19e41dc2ec15b
Actual models with stochastic override behaviour |
Python Source Code - 6.6 KB -
MD5: 4f98a8c6a6ffff6be25b15de8afb6837
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Python Source Code - 7.4 KB -
MD5: 1e41ea7ce286e7a43810bf1743a39049
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Python Source Code - 3.6 KB -
MD5: 3554713e92d8a7606a0b804ce3c8172f
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Python Source Code - 1.6 KB -
MD5: ffd0123b5fa5ff9773e29a4595bd0e4d
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