Research Article
Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 89 - Issue 1 |
| Published: March 2014 |
| Authors: S. Alamelu Mangai, B. Ravi Sankar, K. Alagarsamy |
10.5120/15470-4112
|
S. Alamelu Mangai, B. Ravi Sankar, K. Alagarsamy . Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network. International Journal of Computer Applications. 89, 1 (March 2014), 41-47. DOI=10.5120/15470-4112
@article{ 10.5120/15470-4112,
author = { S. Alamelu Mangai,B. Ravi Sankar,K. Alagarsamy },
title = { Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 89 },
number = { 1 },
pages = { 41-47 },
doi = { 10.5120/15470-4112 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A S. Alamelu Mangai
%A B. Ravi Sankar
%A K. Alagarsamy
%T Taylor Series Prediction of Time Series Data with Error Propagated by Artificial Neural Network%T
%J International Journal of Computer Applications
%V 89
%N 1
%P 41-47
%R 10.5120/15470-4112
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Modeling and forecasting of a time series data is an integral part of the Data Mining. Sun spot numbers observed on the sun are a good candidate for a time series. A number of linear statistical models are discussed in this paper because Taylor series has similarity with an Auto Regressive model. A new algorithm based on Taylor series expansion and artificial neural network is presented. Based on Taylor series algorithm and ARIMA model, the Sunspot numbers are forecasted and compared.
References
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