{rfName}
Qu

Indexed in

License and Use

Icono OpenAccess

Altmetrics

Analysis of institutional authors

Domingo, LaiaAuthorGrande, MarAuthorBorondo, JavierCorresponding Author

Share

October 22, 2024
Publications
>
Article
Sí

Quantifying the Uncertainty of Reservoir Computing: Confidence Intervals for Time-Series Forecasting

Publicated to: Mathematics. 12 (19): 3078- - 2024-10-01 12(19), DOI: 10.3390/math12193078

Authors:

Domingo, Laia; Grande, Mar; Borondo, Florentino; Borondo, Javier
[+]

Affiliations

AgrowingData, Almeria 04001, Spain - Author
Ingenii Inc, New York, NY 10013 USA - Author
Univ Autonoma Madrid, Dept Quim, E-28049 Madrid, Spain - Author
Univ Politecn Madrid, Grp Sistemas Complejos, Madrid 28040, Spain - Author
Univ Pontificia Comillas, ICAI Engn Sch, Alberto Aguilera 23, Madrid 28015, Spain - Author
See more

Abstract

Recently, reservoir computing (RC) has emerged as one of the most effective algorithms to model and forecast volatile and chaotic time series. In this paper, we aim to contribute to the understanding of the uncertainty associated with the predictions made by RC models and to propose a methodology to generate RC prediction intervals. As an illustration, we analyze the error distribution for the RC model when predicting the price time series of several agri-commodities. Results show that the error distributions are best modeled using a Normal Inverse Gaussian (NIG). In fact, NIG outperforms the Gaussian distribution, as the latter tends to overestimate the width of the confidence intervals. Hence, we propose a methodology where, in the first step, the RC generates a forecast for the time series and, in the second step, the confidence intervals are generated by combining the prediction and the fitted NIG distribution of the RC forecasting errors. Thus, by providing confidence intervals rather than single-point estimates, our approach offers a more comprehensive understanding of forecast uncertainty, enabling better risk assessment and more informed decision-making in business planning based on forecasted prices.
[+]

Keywords

Confidence intervalsMarketPricePricesReservoir computingTime seriesUncertainty

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Mathematics due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 29/483, thus managing to position itself as a Q1 (Primer Cuartil), in the category Mathematics. Notably, the journal is positioned above the 90th percentile.

[+]

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-12-21:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 2 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

    It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

    • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
    • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/89129/

    As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

    • Views: 98
    • Downloads: 82
    [+]

    Leadership analysis of institutional authors

    This work has been carried out with international collaboration, specifically with researchers from: United States of America.

    There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (DOMINGO COLOMER, LAIA) and Last Author (Borondo Benito, Francisco Javier).

    the author responsible for correspondence tasks has been Borondo Benito, Francisco Javier.

    [+]

    Awards linked to the item

    The project that gave rise to these results received the support of a fellowship from "la Caixa" Foundation (ID 100010434). The fellowship code is LCF/BQ/DR20/11790028. This work has also been partially supported by the Spanish Ministry of Science, Innovation and Universities, Gobierno de Espana, under Contract No. PID2021-122711NB-C21 and by DG of Research and Technological Innovation of the Community of Madrid (Spain) under Contract No. IND2022/TIC-23716.
    [+]