Day outside of the allowed range for weather prediction.
Correcting Day
Correcting Initial Day to have a five day period.
How to use the Component
The component is divided in two diferent columns: the column of the left hand side has several controls to
visualize data including a menu, two tables and a calendar, and the column of the right hand side has a map and
and area to visualize charts. We describe now these components. The controls on the left column include the following:
Labels Switch: On the top left side, its purpose is to show in the map the id of each sensor.
Filter Switch: On the top center side, its purpose is to show, in the models table, only the models of the sensor
selected in the map.
Models Table: The models table show information about the characteristics and the status of the models that are
or have been trainned. In the bottom left side of the table there are two buttons that allow create new models and delete them.
In addition on the bottom right side there is a button to reload the data of the table.
This last button is important because inmediately after you submit the creation of the model the new model does NOT
show up in the table, the user should press the reload button to be able to see it.
Calendar: The calendar is used to choose the day to be predicted, or the starting day of the period to be predicted.
This is used once the models have been trainned, i.e. their status is zero. By default the selected day corresponds to the current day. In addition
in the calendar. Notice that is a prediction that involves weather is required only few days in the future are susceptible to be predicted. In that particular case the not
allowed days are grey out showing that it cannot be selected.
Loop Table: Shows statistical information about the data from the Loop sensor choosen. Below this table there are two buttoms:
Visualize: Allows to visualize the data associated with the selected sensor to be used for trainning, be aware that visualizing all these data takes generaly a very long time.
Download: Allows to download to your computer the result of a prediction that is shown in the Chart area.
On the map of the right hand side the sensors with data avaiable for the use case selected are show with blue dots.
In order to start with the process to create a new model a sensor has to be choosen by clicking on this blue dot.
Once the loop sensor is selected the avaiable data is shown in the graph area below the map. The historic traffic
stored within the platform is shown in blue, the temperature in green and the precipitation in cyan (for the time being
the temperature and the precipitation are not used for the trainning of models). In addition, other information related
the flow measurements are shown in the table on the left hand side, the aforementioned Loop Table.
Create/Train Model
If a loop sensor is selected (by clicking on it in the map) the trainning of a model can be initiated by pressing the New Model
button located inside the model table. This opens up a new window.
In the case no sensor is selected the process will involve all the sensors and will take a long time.
Once the loop sensor is selected information related the flow measurements are shown in the table on the bottom left hand side.
When the New Model buttom is pressed there is a window opened, in the window the following information can be seen/specified:
id: the identification label for the loop sensor choosen in the map (in the case one loop is selected on the map).
Num Features: number of features considered to create the model:
1: Considers only the time of the day, Hour of the Day (HoD). We call it the *slot* of the day, this corresponds to the time interval
of the day, considering the measuring period of the given sensor.
2: In addition to the previous considers the day of the week (DoW).
3: In addition to the previous considers if the given day is a School day and/or a Holiday or not (SaH).
4: In addition to the previous considers the metereological variables (MET).
5: In addition to the previous considers events.
Once this information is properly set, the creation of the predicting model is started by pressing the Submit button. The information related
to the models that have been created is shown in the Models Table as it can be seen in the following image:
The information that is shown for each model is:
Model: Unique model Id that identifies each model.
id: Id for the Loop sensor associated to the model.
#: Number of features.
Status: Status of the trainning phase:
0: completed
-1: trainning still in process
Score: Score, quality, of model, using the test data set. Only avaiable if the Type is equal to 2 (Random Forest).
This value is better the closer to 1.
Perform Prediction
Once the status of a model is equal to zero the model can be used in order to perform predictions.
The prediction can be performed for a full day, for 4 days or the user can choose a custom period.
The result of the prediction is shown in the graph below the map showing the actual prediction and the confidence
interval associated with it. The prediction is performed for the day selected in the calendar
or starting that day if the period is longer than one day.