Publication detail

Time Series Forecasting Using Artificial Neural Network

VARYŠOVÁ, T.

Original Title

Time Series Forecasting Using Artificial Neural Network

Type

conference paper

Language

English

Original Abstract

The paper aims to verify the ability of artificial neural networks to model and predict time series with seasonal and trend pattern. In this study the effectiveness of data preprocessing and time series analysis is examined, especially deseasonalization and detrending as a basis for further neural network modelling and forecasting. In this paper it is proved that using deseasonalization as data preprocessing method, the best neural network performance is reached with respect to smallest Mean Squared Error showing the difference between outputs and targets. In general the research shows that prior data preprocessing enhances preciseness of further neural network prediction.

Keywords

Time series; seasonal and trend decomposition; forecasting; neural network

Authors

VARYŠOVÁ, T.

RIV year

2015

Released

7. 5. 2015

Publisher

International Business Information Management Association (IBIMA)

Location

Amsterdam

ISBN

978-0-9860419-4-5

Book

Proceedings of the 25th International Business Information Management Association Conference

Pages from

527

Pages to

535

Pages count

9

BibTex

@inproceedings{BUT115320,
  author="Tereza {Šustrová}",
  title="Time Series Forecasting Using Artificial Neural Network",
  booktitle="Proceedings of the 25th International Business Information Management Association Conference",
  year="2015",
  pages="527--535",
  publisher="International Business Information Management Association (IBIMA)",
  address="Amsterdam",
  isbn="978-0-9860419-4-5"
}