ISYE 6501 Final Quiz GT Students exam solution Georgia Institute Of Technology

ISYE 6501 Final Quiz GT Students exam solution Georgia Institute Of Technology

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

Stuvia.com - The Marketplace to Buy and Sell your Study Material GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

Using time-series data to predict the variance of something two time periods in the future

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12/10/2020

Using time-series data to predict the variance of something two time periods in the future

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You have used 1 of 1 attempt

Stuvia.com - The Marketplace to Buy and Sell your Study Material GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

Using time-series data to predict the variance of something two time periods in the future

Submit

You have used 1 of 1 attempt

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

Using time-series data to predict the variance of something two time periods in the future

Submit

You have used 1 of 1 attempt

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

The simulation model needs information about where cars are going from and to, not just the total number of cars.

b. The director has come up with another incorrect idea: GIVEN the fraction of autonomous cars in the city over the past ve years, USE exponential smoothing TO estimate the fraction of autonomous cars in the city in the next 10 years. Then, GIVEN that estimate and an expert estimate of how many of those cars will be going from each part of the city to each other part during rush hour, USE linear regression TO predict the number of lanes required on each major street and highway 10 years from now. Finally, GIVEN the number of cars going between parts of the city during rush hour and the number of lanes on each major street and highway, USE optimization TO nd the quickest route for each car to use.

Select all of the statements below that show a reason why the director's idea is wrong.

Given the small fraction of autonomous vehicles in the city in the past 5 years, exponential smoothing cannot capture the possibility of a major increase in the next 10 years.

Optimization cannot nd the quickest route for a car to use.

Exponential smoothing is not an appropriate model to predict 10 data points in the future based on just 5 data points.

Linear regression cannot predict the number of lanes required based only on the number of cars going between parts of the city.

c. Select all of the possible paths below that could reasonably lead to a good solution.

Estimate the fraction of cars that will be autonomous 10 years from now, and the number of cars that will be going from each part of the city to each other part during rush hour 10 years from now. Determine the maximum number of lanes that can be built based on budget estimates. Estimate the average commute time based on that number of lanes. If the average is above 20 minutes, plan to charge tolls for using certain congested roads during rush hour, and determine how to set those toll prices so that the average commute is below 20 minutes.

Obtain expert estimates of the number of human-driven and autonomous cars going from each part of the city to each other part during rush hour 10 years from now. Estimate the resulting tra c on each road. Determine how many lanes are required on each road to reduce that tra c so the average commute time is below 20 minutes.

Estimate future population and job locations in various parts of the city. Then, based on those estimates, estimate the number of cars going from each part of the city to each other part during rush hour. Estimate the fraction of cars that will be autonomous. Finally, determine how many lanes are required on each major street and highway to keep average commute time below 20 minutes.

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

d. Select a set of models from the list below, that the director of transportation can put together to determine how large to make each street and highway.

GIVEN past data on neighborhood growth and general city-wide population forecasts, USE linear regression (with an autoregressive component) TO estimate the population 10, 15, and 20 years from now in each area of the city.

GIVEN past data on neighborhood growth and general city-wide population forecasts, USE optimization TO estimate the population 10, 15, and 20 years from now in each area of the city.

GIVEN future population estimates, past data on job locations around the city, and a variety of employment forecasts and expert forecasts about jobs that will be done from a worker's home in the future, USE a random logistic regression forest TO develop a range of scenarios for how many cars will be going from each part of the city to each other part during rush hour.

GIVEN future population estimates, past data on job locations around the city, and a variety of employment forecasts and expert forecasts about jobs that will be done from a worker's home in the future, USE simulation TO develop a range of scenarios for how many cars will be going from each part of the city to each other part during rush hour.

GIVEN a range of estimates of the number of cars going from each part of the city to each other part during rush hour, road size restrictions, an expert estimate of the fraction of autonomous cars, and a function that estimates tra c speed based on number of human-driven and autonomous cars and number of lanes, USE optimization TO determine how many lanes each major street and highway should have to keep the average commute time below 20 minutes in 90% of the scenarios.

GIVEN a range of estimates of the number of cars going from each part of the city to each other part during rush hour, road size restrictions, an expert estimate of the fraction of autonomous cars, and a function that estimates tra c speed based on number of human-driven and autonomous cars and number of lanes, USE linear regression TO determine how many lanes each major street and highway should have to keep the average commute time below 20 minutes in 90% of the scenarios.

It has been predicted that if all cars are autonomous, they'll get along much better on the road (unlike humans, who sometimes cut in front of each other to get ahead, causing slowdowns behind them) and commute times will be reduced.

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

GT Students | Final Quiz | ISYE6501x Courseware | edX

12/10/2020

Stuvia.com - The Marketplace to Buy and Sell your Study Material GT Students | Final Quiz | ISYE6501x Courseware | edX

This is the end of the Final Quiz. Please make sure that you submit all your answers before the time runs out. There is no overall Submit button.

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12/10/2020

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