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However, because the number of possible dashboards is very large, it would be impossible to rank each possible one individually.
For the dashboard and mushroom constraints, we have three neurons in the hidden layer whereas we have five for breast-cancer-wisconsin and house-votes-84.
In addition, the dashboard has to fit into a space that is different for every car.
The computed surface corresponds to the global surface of the actual items and not of the dashboard they define, which is larger.
See their demo page for a video that shows the various elements of their dashboard.
Every problem comprises the set of 22 variables describing a dashboard, the dashboard constraint, and some constraints specific to each problem.
By adding information on the surface occupied by each item, we can, for example, find the best dashboard that has the minimum item surface.
The system is installed behind the vehicle's dashboard with its sensor positioned at the end of a protruding small coil.
Finding a dashboard meeting all requirements and following customer preferences is a constraint satisfaction problem.
Hence, it is better to ask the users only on a few examples and to model the concept of "good dashboard" as a partially defined constraint.
Partially defined constraints in constraint-based design modeling of customer preferences as a partially defined constraint allows the system to "invent" new dashboards that are acceptable within the learned concept.
A database of customer tastes has been created by presenting examples of dashboards to a panel of drivers and asking them to select the "good" ones.
Hence, producing a good design for a dashboard is a clever mixture between functionality, design, and anticipation of consumer taste.
This gives drivers recommended routes to their destination using an electronic display fitted to the dashboard of their vehicles.
It is the red light on the dashboard that warns local authorities that there will be a loss of money.