AP47: Multi-objective optimisation and machine learning for climate-friendly building design
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Python Source Code - 2.3 KB - MD5: 9df7927bdcfbda8ac1491fd967dd5615
Defines the schema for building geometry data.
Python Source Code - 6.8 KB - MD5: e7d4a6ad80383ffddcd925287e3ce3cf
Utilities for writing and reading cached preprocessing outputs to/from disk.
Python Source Code - 22.1 KB - MD5: edd1acbc6233b2822ac0fd790bd6f7ab
Implements the core geometric and physical calculations (e.g. surface areas, orientation weighting) underlying feature extraction.
JSON - 3.7 MB - MD5: 320dd038f746ca0c91a42bbd247020f3
Raw simulation input data (geometry, construction, climate) for design space scenario 01.
JSON - 3.5 MB - MD5: 1439cbd3bc00e8a2c401b6c12e751950
Raw simulation input data (geometry, construction, climate) for design space scenario 02.
JSON - 4.1 MB - MD5: 59775c1b41e0c3ae5439b1572846c200
Raw simulation input data (geometry, construction, climate) for design space scenario 03.
JSON - 4.2 MB - MD5: e35bd6947224e0e0cf6a3bc4c25980d3
Raw simulation input data (geometry, construction, climate) for design space scenario 04.
JSON - 4.2 MB - MD5: 5f96d2e1c1b48f3eb93dee1a66574c04
Raw simulation input data (geometry, construction, climate) for design space scenario 05.
JSON - 3.8 MB - MD5: e8c384f4fa902355633971d33ba049ff
Raw simulation input data (geometry, construction, climate) for design space scenario 06.
JSON - 4.2 MB - MD5: dec2de5453521e8f77e616be434fcdd5
Raw simulation input data (geometry, construction, climate) for design space scenario 07.
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