<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Recently, time series forecasting modelling in the Consumer Price Index (CPI) has attracted the attention of the scientific community. Several research projects have tackled the problem of CPI prediction for their countries using statistical learning, machine learning and deep neural networks. The most popular approach to CPI in several countries is the Autoregressive Integrated Moving Average (ARIMA) due to the nature of the data. This paper addresses the Cuban CPI forecasting problem using Transformer with attention model over univariate dataset. The fine tuning of the lag parameter shows that Cuban CPI has better performance with small lag and that the best result was in p = 1. Finally, the comparative results between ARIMA and our proposal show that the Transformer with attention has a very high performance despite having a small data set.</p>
</abstract>

Recently, time series forecasting modelling in the Consumer Price Index (CPI) has attracted the attention of the scientific community. Several research projects have tackled the problem of CPI prediction for their countries using statistical learning, machine learning and deep neural networks. The most popular approach to CPI in several countries is the Autoregressive Integrated Moving Average (ARIMA) due to the nature of the data. This paper addresses the Cuban CPI forecasting problem using Transformer with attention model over univariate dataset. The fine tuning of the lag parameter shows that Cuban CPI has better performance with small lag and that the best result was in p = 1. Finally, the comparative results between ARIMA and our proposal show that the Transformer with attention has a very high performance despite having a small data set.

Cuban Consumer Price Index Forecasting Through Transformer with Attention

Universidad de las Ciencias Informáticas

Journal of Automation, Mobile Robotics and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Cuban Consumer Price Index Forecasting Through Transformer with Attention"}

Recently, time series forecasting modelling in the Consumer Price Index (CPI) has attracted the attention of the scientific community. Several research...

Cuban Consumer Price Index Forecasting Through Transformer with Attention

Online veröffentlicht: 26. Jan. 2024

Seitenbereich: 12 - 17

Eingereicht: 10. Jan. 2023

Akzeptiert: 01. Aug. 2023

DOI: https://doi.org/10.14313/jamris/2-2023/11

Schlüsselwörter
Consumer price index, Time series forecasting, Transformer with attention, ARIMA, LSTM

© 2023 Reynaldo Rosado et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Cuban Consumer Price Index Forecasting Through Transformer with Attention

Online veröffentlicht: 26. Jan. 2024

Seitenbereich: 12 - 17

Eingereicht: 10. Jan. 2023

Akzeptiert: 01. Aug. 2023

DOI: https://doi.org/10.14313/jamris/2-2023/11

SchlüsselwörterConsumer price index, Time series forecasting, Transformer with attention, ARIMA, LSTM

© 2023 Reynaldo Rosado et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Consumer price index, Time series forecasting, Transformer with attention, ARIMA, LSTM