Data · dataset · 2026
Code for: Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method
Listed in DaRUS
This code provides the data preprocessing framework used in the publication "Towards Flexible Building Energy Surrogate Models: A Novel Feature Representation Method", designed to generate flexible, physically meaningful feature representations for surrogate modeling of building energy performance.
Description
The framework extracts fixed-length feature vectors directly from building geometry, construction assemblies, and climate data, offering an alternative to conventional design-parameter-based inputs.
Four representations are supported: a conventional parameter-based baseline and three parameter-independent alternatives. Parameter-based features (baseline), using the raw design parameters of a given design space, Global aggregated features, summarizing geometric, material, and climatic quantities via sums, means, and extrema into a compact vector, Coarse directional features, capturing orientation-dependent effects across six cardinal directions, and Fine directional features, resolving orientation dependence further using a 302-patch orientation discretization.
Read the rest (2 more)
Because these representations are derived from the physical building description rather than a specific parameterization, they can in principle generalize across varying design spaces. The target objective computed by the pipeline is annual heating energy demand. The software is implemented as a flexible, extensible prototype supporting integration with custom datasets and design space exploration workflows.
For more information on setup, usage, and citation, please refer to the README.md file included in the repository.
Links
Where it is published
- Dataverse dataset page darus.uni-stuttgart.de/dataset.xhtml?persistentId=doi%3A10.18419%2FDARUS-6306 ↗
landing page · from darus uni stuttgart de
- DOI doi.org/10.18419/darus-6306 ↗
DOI / persistent id · from darus uni stuttgart de
Catalogue records · 1
- Dataverse API darus.uni-stuttgart.de/api/datasets/:persistentId/?persistentId=doi%3A10.18419%2FDARU… ↗
metadata API · from darus uni stuttgart de
Topics
- Stated by source
- Computer and Information Science · Engineering
- From keywords
- Computer Science & AI · Engineering · Machine learning · Simulation
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DaRUS | doi:10.18419/DARUS-6306 | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4611 | mapping · darus uni stuttgart de | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].dataverse_subject:computer-and-information-science | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:engineering | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[method].local:method:simulation | mapping · darus uni stuttgart de | vocabulary-mapper@1.0.0 | keywords['Simulation'] |
| created_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| description | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /description |
| publication_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| title | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /name |
| updated_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| version_label | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 |