When nonlinearity is present, time series prediction becomes a difficult task. The ASHRAE Energy Predictor Shootout II competition problem is no exception; the difficulty is amplified because analytical equations for describing the dynamics are formidable, if not impossible. The problem belongs to a rather interesting class of problems that can arise in many practical situations. A Bayesian approach is taken in performing nonlinear regression on the ASHRAE Predictor Shootout II time series data. The Bayesian framework enables one to perform the regression in a hierarchical manner, i) level 1 – estimation of the parameters; ii) level 2 – estimation of hyperparameters; and iii) level 3 – model comparison. The prediction results appear to be reasonable.
KEYWORDS: year 1996, algorithms, calculating, expert systems, dynamic programming
Citation: Symposium, ASHRAE Trans. 1996, Vol.102, Part 2
Product Details
- Published:
- 1996
- File Size:
- 1 file , 510 KB
- Product Code(s):
- D-16597
