@inproceedings{5def674ee50d4b8f914392e09dc751c0,
title = "Artificial Neural Network Models for Time Series Smoothing and Holt Trend Analysis",
abstract = "We show how to create Artificial Neural Network based models for performing time series exponential-like smoothing and the well-known Holt time series analysis. Our work fares well compared to the well known Holt time series analysis and prediction method, while avoiding the burden of searching for the parameters of the model. We present the theoretical justification of the connection between the two models and experimental results showing the similarities of these models.",
keywords = "Artificial Neural Networks, prediction, time series analysis",
author = "Kazeem Bankole and Felix Hamza-Lup and Iacob, {Ionut E.}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 16th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2024 ; Conference date: 27-06-2024 Through 28-06-2024",
year = "2024",
doi = "10.1109/ECAI61503.2024.10607440",
language = "English",
series = "Proceedings of the 16th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of the 16th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2024",
address = "United States",
}
