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Probabilistic load forecasting competition

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By Topics | Advanced Analytics Analytics
Dr. Tao Hong
Dr. Tao Hong

So you think you know how to forecast?

Now is your chance to prove it, by participating in a probabilistic load forecasting competition run by my friend (and former SAS colleague), Dr. Tao Hong.

Currently a professor at UNC Charlotte and director of the Big Data Energy Analytics Laboratory (BigDEAL), Tao is opening his class competition to students and professionals outside of his Energy Analytics course. See his October 12 Energy Forecasting blog for information, including these competition rules:

  • The competition will start on 10/22/2015, and end on 11/25/2015.
  • The historical data will be released on 10/22/2015.
  • The year-ahead hourly probabilistic load forecast is due on 11:45am ET each Wednesday starting from 10/28/2015.
  • The exam is individual effort. Each student form a single-person team. No collaboration is allowed.
  • The student can not use any data other than what's provided by Dr. Tao Hong and the U.S. federal holidays.
  • Pinball loss function is the error measure in this competition.
  • The benchmark will be provided by Dr. Tao Hong. A student receive no credit if not beating the benchmark nor ranking top 6 in the class.
  • No late submission is allowed.

If you are interested in joining the competition, please email Dr. Tao Hong (at hongtao01@gmail.com) for more details.

Tags Dr. Tao Hong energy analytics energy forecasting forecasting competition probabilistic load forecasting SAS UNC Charlotte
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About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and formerly a Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and former editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike received the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

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