HomeWork-TimeSeriesMining-Sol

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University of South Florida *

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6136

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Industrial Engineering

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Apr 3, 2024

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docx

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Homework: Time Series Mining Question 1. A dry cleaner uses exponential smoothing to forecast equipment usage at its main plant. August usage was forecasted to be 88 percent of capacity; actual usage was 89.6 percent of capacity. A smoothing constant of .1 is used. a. Prepare a forecast for September. Ans: Exponential smoothing forecast for September with alpha = 0.10: 88 + 0.10(89.6 – 88) = 88.16 (round to two decimals) b. Assuming actual September usage of 92 percent, prepare a forecast for October usage. Ans: Exponential smoothing forecast for October with alpha = 0.10: 88.16 + 0.10(92 – 88.16) = 88.54 (round to two decimals) Question 2: An electrical contractor’s records during the last five weeks indicate the number of job requests: Predict the number of requests for week 6 using each of these methods: a. Naive. b. A four-period moving average. c. Exponential smoothing with .30. Use 20 for week 2 forecast. Ans: Given: Week Requests 1 20 2 22 3 18 4 21 5 22 a. Naïve approach forecast for Week 6 = Demand in Week 5 = 22 b. Four-period moving average forecast for Week 6: 22 + 18 + 21 + 22 4 = 20.75 (round to two decimals)
Homework: Time Series Mining c. Exponential smoothing with alpha = 0.30 and a Week 2 Forecast = 20 (round to two decimals): F 3 = 20 + 0.30(22 – 20) = 20.60 F 4 = 20.60 + 0.30(18 – 20.6) = 19.82 F 5 = 19.82 + 0.30(21 – 19.82) = 20.17 F 6 = 20.17 + 0.30(22 – 20.17) = 20.72 Question 3: From the following graph, determine the equation of the linear trend line for time- share sales for Glib Marketing, Inc. Ans: Slope of the line is estimated by Rise/Run = (300-500)/(10-0) = -200/10 = -20.00. The Y Intercept = 500.
Homework: Time Series Mining Question 4: Solution: 7. a. t Y t*Y t 2 1 220 220 1 2 245 490 4 3 280 840 9 4 275 1,100 16 5 300 1,500 25 6 310 1,860 36 7 350 2,450 49 8 360 2,880 64 9 400 3,600 81 10 380 3,800 100 11 420 4,620 121 12 450 5,400 144 13 460 5,980 169 14 475 6,650 196 15 500 7,500 225 16 510 8,160 256 17 525 8,925 289 18 541 9,738 324 171 7,001 75,713 2,109
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