Description

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