Time series model to forecast the surface temperature of the sea in the coastal area of Paita (Perú)

Authors

  • Oscar J. M. Peña Cáceres Universidad Nacional de Piura
  • Manuel A. More More Universidad Nacional de Piura
  • Rudy Espinoza Nima Universidad Nacional de Piura
  • Henry Silva Marchan Universidad Nacional de Tumbes

DOI:

https://doi.org/10.37467/revtechno.v11.4458

Keywords:

El Niño Phenomenon, Sea Surface Temperature, Time series, Artificial Neural Network, Population

Abstract

Artificial intelligence techniques have evolved and strengthened, allowing the development of transversal proposals that watch over and safeguard the integrity of the human being. The objective of this study is to develop a time series that forecasts the Sea Surface Temperature (SST) on an average daily scale in the coastal area of Paita, Perú. The methodology used focused on five phases, from data collection to model validation. The results obtained reveal that there is a margin of error of 3.96% on the SST on a weekly average scale and a difference of 0.05 to 1.42, on a daily basis.

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Published

2022-12-29

How to Cite

Peña Cáceres, O. J. M., More More, M. A., Espinoza Nima, R., & Silva Marchan, H. . (2022). Time series model to forecast the surface temperature of the sea in the coastal area of Paita (Perú). TECHNO REVIEW. International Technology, Science and Society Review Revista Internacional De Tecnología, Ciencia Y Sociedad, 11(5), 1–11. https://doi.org/10.37467/revtechno.v11.4458

Issue

Vol. 11 No. 5 (2022): Monograph: "Cutting-edge innovation from pre- and post-doctoral academic texts"

Section

Research Articles (Special Issue)

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