Prediction of convective clouds formation using evolutionary neural computation techniques
| Autor: | Pedro Antonio Gutiérrez, David Guijo-Rubio, Juan Carlos Fernández, Pablo Salvador-González, Antonio M. Gómez-Orellana, C. Casanova-Mateo, Sancho Salcedo-Sanz, César Hervás-Martínez |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Artificial neural network Computer science Evolutionary algorithm Basis function Time horizon 02 engineering and technology Sigmoid function computer.software_genre 020901 industrial engineering & automation Models of neural computation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Radial basis function Data mining computer Software |
| Zdroj: | Neural Computing and Applications. 32:13917-13929 |
| ISSN: | 1433-3058 0941-0643 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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