TY - DATA
T1 - Data underlying the research on On-line warning system for pipe burst using Bayesian dynamic linear models
PY - 2022/09/15
AU - Renato Henriques da Silva
AU - Alexandra M. Schmidt
AU - Sophie Duchesne
AU - Nicolas Fortin St-Gelais
UR - https://data.4tu.nl/articles/dataset/Data_underlying_the_research_on_On-line_warning_system_for_pipe_burst_using_Bayesian_dynamic_linear_models/17169383/3
DO - 10.4121/17169383.v3
KW - pipe break
KW - water flow
KW - dynamic linear model
N2 - <p>The dataset contains the following items:</p>
<p><br></p>
<p>- dma1_flow.txt = hourly water flow (m3/h) for district meter area 1</p>
<p>(rows are days, columns are the 24 hours)</p>
<p><br></p>
<p>- dma1_pressure.txt = hourly pressure (psi) for district meter area 1</p>
<p>(rows are days, columns are the 24 hours)<br>
</p>
<p><br></p>
<p>- temperature.txt = hourly temperature (Celcius)</p>
<p>(rows are days, columns are the 24 hours)<br>
</p>
<p><br></p>
<p>- wk_dummy.txt = dummy variable indicating whether its a workday or a weekend</p>
<p>(rows are days, columns are the 2 dummy variables)<br>
</p>
<p><br></p>
<p>- dates : dates of the recordings</p>
<p>(rows are days)<br>
</p>
<p><br></p>
<p>dlm_script.R : a R script to run the dynamic linear model with the example dataset.</p>
<p><br></p>
ER -