Modelling district heating demand: A synthetic dataset for two residential neighbourhoodsZenodo
The extensive artificial datasets developed in this study capture the energy demands of two districts and, with reasonable constraints, emulate monitoring campaigns typically conducted on-site in inhabited houses. Generated datasets are the following, one 1) representing low-performing building stoc...
Saved in:
| Main Authors: | Katia Ritosa, Ina De Jaeger, Dirk Saelens, Staf Roels |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
|
| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925000265 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Towards Synthetic Augmentation of Training Datasets Generated by Mobility-on-Demand Service Using Deep Variational Autoencoders
by: Martin Gregurić, et al.
Published: (2025-04-01) -
What makes neighbourhood-level commercial centres attractive for neighbourhood residents?
by: Archiman Biswas, et al.
Published: (2024-12-01) -
Semantic network analysis of spatial gene sequence in Dabaodao neighbourhood
by: Jun Dong, et al.
Published: (2025-05-01) -
Comparing variable neighbourhood search algorithms for the direct aperture optimisation in radiotherapy
by: Mauricio Moyano, et al.
Published: (2025-08-01) -
Living in an unhealthy neighbourhood impacts individual employment status
by: Patricia Ots, et al.
Published: (2025-07-01)