Researchers compiled data set RWY-96 to train a machine learning model to predict which of several existing scheduling algorithms will minimize delays in a given airport’s runway operations. Consisting of 9,600 simulated days of operations, each divided into forty-eight half-hour time slots, the data set systematically varies four factors: arrival demand profiles (eight scenarios, including sudden surges), weather-related reductions in runway capacity (none, moderate, and severe), the proportion of heavy aircraft in the traffic mix (high and low), and runway configuration (single and dual).
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Verbal·Information and Ideas·Inferences
mediumWhich statement about data set RWY-96 is best supported by the text?
A
The data set gives greater weight to severe-weather scenarios than to other conditions because such scenarios cause the longest delays.
B
The data set combines records collected at actual airports with simulated days that fill gaps in those records.
C
The data set was designed to expose the model to a deliberately varied range of hypothetical operating conditions so that the model can learn to match algorithms to circumstances.
D
The data set reflects the relative frequency with which different combinations of operating conditions occur at real airports.