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Authors: Conor Ryan 1 ; Meghana Kshirsagar 1 ; Purva Chaudhari 2 and Rushikesh Jachak 2

Affiliations: 1 Biocomputing Developmental Systems, University of Limerick, Ireland ; 2 Department of Computer Science, Government College of Engineering, Aurangabad, India

ISBN: 978-989-758-395-7

Keyword(s): Time Series Forecasting, Grammatical Evolution, Genetic Programming.

Abstract: Time series forecasting is a technique that predicts future values using time as one of the dimensions. The learning process is strongly controlled by fine-tuning of various hyperparameters which is often resource extensive and requires domain knowledge. This research work focuses on automatically evolving suitable hyperparameters of time series for level, trend and seasonality components using Grammatical Evolution. The proposed Grammatical Evolution Time Series framework can accept datasets from various domains and select the appropriate parameter values based on the nature of dataset. The forecasted results are compared with a traditional grid search algorithm on the basis of error metric, efficiency and scalability.

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Paper citation in several formats:
Ryan, C.; Kshirsagar, M.; Chaudhari, P. and Jachak, R. (2020). GETS: Grammatical Evolution based Optimization of Smoothing Parameters in Univariate Time Series Forecasting.In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-395-7, pages 595-602. DOI: 10.5220/0008963305950602

@conference{icaart20,
author={Conor Ryan. and Meghana Kshirsagar. and Purva Chaudhari. and Rushikesh Jachak.},
title={GETS: Grammatical Evolution based Optimization of Smoothing Parameters in Univariate Time Series Forecasting},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2020},
pages={595-602},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008963305950602},
isbn={978-989-758-395-7},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - GETS: Grammatical Evolution based Optimization of Smoothing Parameters in Univariate Time Series Forecasting
SN - 978-989-758-395-7
AU - Ryan, C.
AU - Kshirsagar, M.
AU - Chaudhari, P.
AU - Jachak, R.
PY - 2020
SP - 595
EP - 602
DO - 10.5220/0008963305950602

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