Data underlying the research on On-line warning system for pipe burst using Bayesian dynamic linear models

Datacite citation style:
Henriques da Silva, Renato; Schmidt, Alexandra M.; Duchesne, Sophie; Fortin St-Gelais, Nicolas (2022): Data underlying the research on On-line warning system for pipe burst using Bayesian dynamic linear models. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/17169383.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version: version 3 - 2022-09-15 (latest) version 2 - 2022-04-12
version 1 - 2022-04-04
usage stats
688
downloads
1212
views
1
citations
time coverage
2015-01-01 to 2016-12-31
licence
cc-0.png logo CC0
The dataset contains the following items:

- dma1_flow.txt = hourly water flow (m3/h) for district meter area 1
- dma2_flow.txt = hourly water flow (m3/h) for district meter area 2
(rows are days, columns are the 24 hours)

- dma1_pressure.txt = hourly pressure (psi) for district meter area 1
- dma2_pressure.txt = hourly pressure (psi) for district meter area 2
(rows are days, columns are the 24 hours)

- temperature.txt = hourly temperature (Celcius)
(rows are days, columns are the 24 hours)

- wk_dummy.txt = dummy variable indicating whether its a workday or a weekend
(rows are days, columns are the 2 dummy variables)

- dates : dates of the recordings
(rows are days)

history
  • 2022-04-04 first online, published, posted
publisher
4TU.ResearchData
format
txt, R-script
funding
  • Mitacs IT15343
organizations
Halifax Water

DATA

files (8)