Preprint / Versión 1

Exploration of Climate Data and Temperature Forecasting using Machine Learning

article.authors6a0547b3d4839

DOI:

https://doi.org/10.1590/SciELOPreprints.9174

Keywords:

machine learning, Geographical data, Temperature prediction

Resumen

In this short communication, a concept has been presented to model geographical data to predict future temperature of Tabuk, region. Machine learning has been applied to the weather station data to develop a prediction model. The preliminary results are promising and encouraging and are envisaging to further this research towards the determination of unknown temperature rise in the region. This is important to mention here, that the problem has been formulated as a Regression problem, NOT as a classification problem. Hence, applying Convolutional neural networks is not possible, due to the non-existence of classes or converting the temperature values to classes does not make any sense. Hence, this is defined as a regression problem which achieved encouraging desirable results.

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Postado

11/07/2024

Cómo citar

Exploration of Climate Data and Temperature Forecasting using Machine Learning. (2024). In SciELO Preprints. https://doi.org/10.1590/SciELOPreprints.9174

Serie

Ciencias Exactas y de la Tierra

Plaudit

Declaración de datos

  • Los datos de investigación están incluidos en el propio manuscrito