Title :
Introducing Flow Field Forecasting
Author :
Frey, Michael ; Caudle, Kyle
Author_Institution :
Math. Dept., Bucknell Univ., Lewisburg, PA, USA
Abstract :
A machine learning methodology, called flow field forecasting, is proposed for statistically predicting the future of a univariate time series. Flow field forecasting draws information from the interpolated flow field of an observed time series to build a forecast step-by-step. Flow field forecasting is presented with examples, a discussion of its properties relative to other common forecasting techniques, and a statistical error analysis.
Keywords :
error analysis; forecasting theory; learning (artificial intelligence); time series; flow field forecasting; flow field interpolation; machine learning methodology; statistical error analysis; univariate time series; Forecasting; Ground penetrating radar; History; Interpolation; Skeleton; Time series analysis; Vectors; extrapolation; prediction; standard error; time series;
Conference_Titel :
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4577-2134-2
DOI :
10.1109/ICMLA.2011.82
