DocumentCode
561199
Title
Introducing Flow Field Forecasting
Author
Frey, Michael ; Caudle, Kyle
Author_Institution
Math. Dept., Bucknell Univ., Lewisburg, PA, USA
Volume
1
fYear
2011
fDate
18-21 Dec. 2011
Firstpage
395
Lastpage
400
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/ICMLA.2011.82
Filename
6147004
Link To Document