PPT-Lecture #17: Ridership Forecasting

Course Instructor Course Semester Course Number Materials developed by C Brakewood K Watkins and J LaMondia Outline Overview of transit demand Methods to forecast ridership changes. Free to share, print, make copies and changes. Get yours at . www.boundless.com. Available on the Boundless Teaching Platform. Using Boundless Presentations. The Appendix. The appendix is for you to use to add depth and breadth to your lectures. You can simply drag and drop slides from the appendix into the main presentation to make for a richer lecture experience.. Instead of . “I’m just using my ‘skip days’ now instead of when the weather is nice,” Harbor said.. City Bus has also seen a rise in business due to the weather, according to spokeswoman Joy Johnson. Ridership is up 37 percent, and delays of 10 to 20 minutes are possible of many routes that serve Purdue’s campus. . A forecast is a prediction or estimation of future situation. It is an objective assessment of future course of action. Since future is uncertain, no forecast can be per cent correct. Forecasts can be both physical as well as financial in nature. The more realistic the forecasts, the more effective decisions can be taken for tomorrow.. Thursday, August 25, 2016. 2:30PM –4:00 PM. Pat Walker, Pat Walker Consulting LLC. Tom Duensing, Assistant City Manager, . City of Glendale. 1. Presentation Objectives. Introduction/Overview. Overview of Budget Process. You should be able to:. LO 3.1 List features common to all forecasts. LO 3.2 Explain why forecasts are generally wrong. LO 3.3 List elements of a good forecast. LO 3.4 Outline the steps in the forecasting process. USDA Foods. The importance of forecasting to the supply chain and cost effective procurement. Existing tools for forecasting. Promoting good supply chain management, procurement and forecasting. In this Training. Presented by Christopher J. Swanson. Government Finance Research Group. www.MuniCast.com. 1. Financial Modeling & Forecasting Smart Practices. www.MuniCast.com. 2. Smart Practices. Annual Forecasting Model – Key Elements. Open Forum. Monday. , . November 25, . 2013. Aggie Spirit. Student Population Density Map . (10/2013). Proposed Off Campus . Route Changes. Route 31. Route 33. Route 34. Route 35. Route 36.  . Off Campus Ridership. Pravin. Kumar . Agrawal. Assistant Professor. Department of Business Management. CSJMU. Why Firm Forecast Exchange rates. MNCs need exchange rate forecasts for their:. Hedging Decisions: if the exchange rate remain stable then they will not hedge. LO18–2: Evaluate demand using quantitative forecasting models.. LO18–3: Apply qualitative techniques to forecast demand.. LO18–4: Apply collaborative techniques to forecast demand.. McGraw-Hill/Irwin. Özlem. . Akçay. Kasapoğlu. ,. Associate. . Professor. . Istanbul University. . Faculty. of . Business. . Operations. . Management. . Department. ozlemak. @. istanbul. .edu.tr. Abstract. Forecasting is one of the first steps in... A hybrid dynamic microsimulation approach. IMA Conference Dec ‘20. We have a strong track record in microsimulation. Recent developments:. AnyLogic Translation. Move to INFORM2. Working Age Modelling & Forecasting. REPUBLIC of TURKEY. MINISTRY of TREASURY & FINANCE. Contents. Forecasting Inflows. 2. 1. Forecasting . Outlows. 3. Institutional. . Capacity. & . Reporting. 4. Cash . Forecasting. . and. . - . Better forecasting for rising or falling demand. - Coping with seasonal demand. - Alternative techniques. Figure 13.1 Forecasting Trend. Figure 13.2 Double exponential model. Y=. bx. + d. b. a. Time Periods x.