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External Climate Data Extraction Using the Forward Feature Selection Method in the Context of Occupational Safety

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Computational Science and Its Applications – ICCSA 2022 Workshops (ICCSA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13378))

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Abstract

Global climate changes and the increase in average temperatures are some of the major contemporary problems that have not been considered in the context of external factors to increase accident risk. Studies that include climate information as a safety parameter in machine learning models designed to predict the occurrence of accidents are not usual. This study aims to create a dataset with the most relevant climatic elements, to get better predictions. The results will be applied in future studies to correlate with the accident history in a retail sector company to understand its impact on accident risk. The information was collected from the National Oceanic and Atmospheric Administration (NOAA) climate database and computed by a wrapper method to ensure the selection of the most features. The main goal is to retain all the features in the dataset without causing significant negative impacts on the prediction score.

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Acknowledgments

This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the Project Scope UIDB/05757/2020 and NORTE-01-0247-FEDER-072598 iSafety: Intelligent system for occupational safety and well-being in the retail sector.

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Authors and Affiliations

  1. Research Center in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253, Bragança, Portugal

    Felipe G. Silva, Inês Sena, Laires A. Lima, Florbela P. Fernandes, Maria F. Pacheco, Clara B. Vaz, José Lima & Ana I. Pereira

Authors
  1. Felipe G. Silva
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  2. Inês Sena
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  3. Laires A. Lima
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  4. Florbela P. Fernandes
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  5. Maria F. Pacheco
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  6. Clara B. Vaz
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  7. José Lima
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  8. Ana I. Pereira
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Corresponding author

Correspondence to Felipe G. Silva .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Østfold University College, Halden, Norway

    Sanjay Misra

  4. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  5. University of Cagliari, Cagliari, Italy

    Chiara Garau

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Silva, F.G. et al. (2022). External Climate Data Extraction Using the Forward Feature Selection Method in the Context of Occupational Safety. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13378. Springer, Cham. https://doi.org/10.1007/978-3-031-10562-3_1

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  • DOI: https://doi.org/10.1007/978-3-031-10562-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-10561-6

  • Online ISBN: 978-3-031-10562-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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