.A 45 kW rated solar power system has its power output and the Solar irradiance on the PV system measured during daylight hours over a day. Based on the following data, create a scatter plot of the power output of the PV system vs the solar irradiance and comment on the relationship between the two. Based on the data, can you tell which season this day was in? Solar Irradiance on the PV system (kW/m²) 0 0.079 0.333 0.571 0.751 0.86 0.914 0.93 0.904 0.803 0.606 0.345 0.054 Power output from the PV system (kW) 0 3.098 12.438 20.124 25.703 28.498 29.587 29.69 28.798 26.264 20.434 12.223 2
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- At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.Use this data and build a model to forecast annual maintenance expenses based on the weekly usage in hours. If the machine is used for 38.4 hours, what should I expect my annual maintenance expenses to be? (Keep one decimal place) Weekly Usage (hours) Annual Maintenance Expense 13 17.0 10 22.0 20 30.0 28 37.0 32 47.0 17 30.5 24 32.5 31 39.0 40 51.5 38 40.0An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data: (4 year ago Quantity sold was 10842), (3 year ago Quantity sold was 11881 ), (2 year ago Quantity sold was 16064 ) and the last year Quantity sold was 19273 . The previous trend line had predicted 12250 for three years ago, 13000 for two years ago and 13750 for last year. What was the mean absolute percent error (MAPE) for these forecasts? a. 16.95 b. 2739 c. 0.17 d. 2985
- Consider the following from an estate agent business: Month Houses Sold Jan 380 Feb 360 Mar 390 Apr 400 May 390 June 380 July 394 Aug 454 Sep 460 Oct 460 Nov 430 Dec 370 a) Calculate the three point moving averages (quarters) and seasonal variation for the above data b) A detective figures he has a one in nine chance of recovering stolen property. His out-of-pocket expenses for the investigation are $9,000. If he is paid his fee only if he recovers the stolen property, what should he charge clients in order to breakeven? c) At the races, your horse, has a probability of 1/20 of coming 151, 1/10 of coming 2nd and a probability of ¼ in coming 3rd. First place pays $4,500 to the winner, second place $3,500 and third place $1,500. Hence, is it worth entering the race if it costs $1,000? d) Your company plans to invest in a particular…DFC Company has recorded the past years sales for the company: Year(t) Sales(x) (in Million Pesos) 2011(1) 2012(2) 2013(3) 2014(4) 2015(5) 2016(6) 2017(7) 2018(8) 2019(9) 2020(10) 219 224 268 272 253 284 254 278 282 298 Use the naïve model. Compute for MAE and MSE Use a three period moving average. Compute for the MAE and MSE Use the simple exponential smoothing to make a forecasting table. Compute the MAE and MSE of the forecasts. Alpha = 0.1 Use the least square method to make the forecasting table. Compute the MAE and MSE *** Use excel or r programmingRoom registrations in the Toronto Towers Plaza Hotel have been recorded for the past 9 years. To project future occu-pancy, management would like to determine the mathemati-cal trend of guest registration. This estimate will help the hotel determine whether future expansion will be needed. Given the following time-series data, develop a regression equation relat-ing registrations to time (e.g., a trend equation). Then forecast year 11 registrations. Room registrations are in the thousands:Year 1: 17 Year 2: 16 Year 3: 16 Year 4: 21 Year 5: 20Year 6: 20 Year 7: 23 Year 8: 25 Year 9: 24
- 12.2. The manager of the I-85 Carpet Outlet needs to be able to forecast accurately the demand for Soft Shag carpet (its biggest seller). If the manager does not order enough carpet from the carpet mill, customers will buy their carpets from one of the outlet’s many competitors. The manager has collected the following demand data for the past eight months: Month Demand for Soft Shag Carpet (1000 yd)1 52 103 64 85 146 107 98 12 a. Compute a three-month moving average forecast for months 4 through 9. b. Compute a weighted three-month moving average forecast for months 4 through 9. Assign weights of .55, .33, and .12 to the months in sequence, starting with…Sales of Cool-Man air conditioners have grown steadily during the past 5 years: (Round your answers to 2 decimal places.) Forecast Forecast Year Sales (a = 0.30) (a 0.90) 1 450 410.0 410.00 495 3 518 470.60 490.10 4 563 5 584 495.20 6 ? 1. The sales manager had predicted, before the business started, that year 1's sales would be 410 air conditioners. Using exponential smoothing with a weight of a = 0.30, complete the Forecast column to develop forecasts for years 2 through 6. What is the MADa=0.30 ? 2. Using exponential smoothing with a weight of a = 0.90, develop forecasts for years 2 through 6 by completing the Forcast column in the table. What is the MAD-0,90 ? 3. Using the trend projection method, develop a forecasting model to project sales for year 6. 2.The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 Pints Used 360 389 412 378 366 371 a) The forecasted demand for the week of October 12 using a 3-week moving average: to two decimal places). = pints (round your response
- FC.51 Madison Memorial Hopsital is considering purchasing a new ambulance. The decision will rest partly on the anticipated mileage to be driven this year (2023). The miles driven during the past eight years are as follows: Year Miles Driven 2015 2016 2017 2018 2019 2020 2021 2022 3,240 1,211 3,208 3,253 2,169 2,224 1,162 1,074 Using a 4-year moving average, what would be the forecast for the miles to be driven in 2023? (Display your answer to the nearest whole number.) Number Using a 4-year weighted moving average (with last year's weight as 0.5, two years previous as 0.2; three years previous as 0.2, and four years previous as 0.1) what is the forecast for 2023? (Display your answer to the nearest whole number.) NumberTucson Machinery, Inc., manufactures numerically controlled machines, which sell for an average price of $14.0 million each. Sales for these NCMs for the past two years were as follows: Use Exhibit 3.10. QUARTER LAST YEAR I II III IV QUANTITY (UNITS) Y = 14 20 28 18 QUARTER THIS YEAR I II III IV QUANTITY (UNITS) 20 26 30 15 a. Find the equation of a simple linear regression line using Excel. (Round your answers to 3 decimal places.) > Answer is complete but not entirely correct. 18.535 X + 0.630 tThe following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 Pints Used 350 370 410 383 368 374 a) The forecasted demand for the week of October 12 using a 3-week moving average=pints (round your response to two decimal places).