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Prediction of convective clouds formation using evolutionary neural computation techniques

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Abstract

The prediction of convective clouds formation is a very important problem in different areas such as agriculture, natural hazards prevention or transport-related facilities. In this paper, we evaluate the capacity of different types of evolutionary artificial neural networks to predict the formation of convective clouds, tackling the problem as a classification task. We use data from Madrid-Barajas airport, including variables and indices derived from the Madrid-Barajas airport radiosonde station. As objective variable, we use the cloud information contained in the METAR and SPECI meteorological reports from the same airport and we consider a prediction time horizon of 12 h. The performance of different types of evolutionary artificial neural networks has been discussed and analysed, including three types of basis functions (sigmoidal unit, product unit and radial basis function) and two types of models, a mono-objective evolutionary algorithm with two objective functions and a multi-objective evolutionary algorithm optimised by the two objective functions simultaneously. We show that some of the developed neuro-evolutionary models obtain high quality solutions to this problem, due to its high unbalance characteristic.

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Notes

  1. http://weather.uwyo.edu/upperair/sounding.html.

  2. Further information of the parameters considered can be found in [38, 56, 57], whereas, more information regarding the ANNs can be obtained from [37].

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Acknowledgements

This research has been partially supported by the Ministerio de Economía, Industria y Competitividad of Spain (Refs. TIN2017-85887-C2-1-P and TIN2017-85887-C2-2-P) and Consejería de Economía, Conocimiento, Empresas y Universidad de la Junta de Andalucía (Ref. UCO-1261651). D. Guijo-Rubio’s research has been supported by the FPU Predoctoral Program from Spanish Ministry of Education and Science (Grant Ref. FPU16/02128).

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Authors and Affiliations

  1. Department of Computer Science and Numerical Analysis, University of Córdoba, Rabanales Campus, Albert Einstein Building 3rd Floor, 14071, Córdoba, Spain

    David Guijo-Rubio, Pedro A. Gutiérrez, Juan Carlos Fernández, Antonio Manuel Gómez-Orellana & César Hervás-Martínez

  2. Department of Civil Engineering: Construction, Infrastructure and Transport, Universidad Politécnica de Madrid, Madrid, Spain

    Carlos Casanova-Mateo

  3. LATUV, Remote Sensing Laboratory, Universidad de Valladolid, Valladolid, Spain

    Pablo Salvador-González

  4. Department of Signal Processing and Communications, Universidad de Alcalá, Alcalá de Henares, Spain

    Sancho Salcedo-Sanz

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  1. David Guijo-Rubio
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Guijo-Rubio, D., Gutiérrez, P.A., Casanova-Mateo, C. et al. Prediction of convective clouds formation using evolutionary neural computation techniques. Neural Comput & Applic 32, 13917–13929 (2020). https://doi.org/10.1007/s00521-020-04795-w

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