EXC IntCDC Associated Project 47 'Optimisation and Machine Learning for Climate-Friendly Design'

AP47: Multi-objective optimisation and machine learning for climate-friendly building design

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71 to 80 of 137 Results

README.md Jul 21, 2026 - Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method Markdown Text - 5.1 KB - MD5: 7e696c3071f150bfada16b9f312df12e Project documentation describing the repository's purpose, setup, and usage.
representation.py Jul 21, 2026 - Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method Python Source Code - 3.5 KB - MD5: 86387e5f03d18031f96a3e583909c64a Defines the data classes/objects representing a computed feature representation (e.g. its structure, features, and metadata).
weather.py Jul 21, 2026 - Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method Python Source Code - 983 B - MD5: 80ddff107c4dedb97f1489c5e2da2087 Defines the schema for climate/weather time series data.
frontend.tar Apr 20, 2026 - Supplemental Materials for: Evaluating Interactive Visualizations of Multi-Objective Optimization Results for Architectural Design Decision-Making TAR Archive - 6.5 MB - MD5: 305649245203e54297fb856c1b92831e
README.md Apr 20, 2026 - Supplemental Materials for: Evaluating Interactive Visualizations of Multi-Objective Optimization Results for Architectural Design Decision-Making Markdown Text - 2.1 KB - MD5: d33a254bb0ced5bab6f0b549bb291c0e
Opossum.zip Feb 20, 2026 - Opossum ZIP Archive - 194.4 KB - MD5: b89c5c8497df28910bf8bc93e553fa57 The Opossum Repository
GP_00.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 553.7 KB - MD5: 21610e5f675a9c616922962e836f1742
GP_01.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 560.3 KB - MD5: 6a5507abfa6ca21b864210f8a9a720eb
GP_02.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 546.2 KB - MD5: 1790b4a412ea8c0235809e20538e539f
GP_03.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 546.2 KB - MD5: 7a0b79d1f887ac6dd9ce1c7d75fa8b28

README.md

Jul 21, 2026 - Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method

Markdown Text - 5.1 KB -

Project documentation describing the repository's purpose, setup, and usage.

representation.py

Jul 21, 2026 - Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method

Python Source Code - 3.5 KB -

Defines the data classes/objects representing a computed feature representation (e.g. its structure, features, and metadata).

weather.py

Jul 21, 2026 - Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method

Python Source Code - 983 B -

Defines the schema for climate/weather time series data.