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Using Machine Learning Techniques to Recover Prismatic Cirrus Ice Crystal Size from 2-Dimensional Light Scattering Patterns

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Artificial Neural Networks and Machine Learning – ICANN 2016 (ICANN 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9887))

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Abstract

In this paper, we present a prediction model developed to identify particles size of ice crystals in clouds. The proposed model combines a Feed Forward Multi-Layer Perceptron neural network with Bayesian regularization backpropagation and other machine learning techniques for feature reduction with Principal Component Analysis and rotation invariance with Fast Fourier Transform. The proposed solution is capable of predicting the particle sizes with normalized mean squared error around 0.007. However, the proposed network model is not able to predict the size of very small particles (between 3 and 10 \({\upmu }\)m size) with the same precision as for the larger particles. Therefore, in this work we also discuss some possible reasons for this problem and suggest future points that need to be analysed.

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Authors and Affiliations

  1. Connectionism and Cognitive Science Lab, Deparment of Informatic and Statistic, Federal University of Santa Catarina, Florianopolis, SC, Brazil

    Daniel Priori, Giseli de Sousa & Mauro Roisenberg

  2. Science and Technology Research Institute, University of Hertfordshire, Hatfield, Herts, UK

    Giseli de Sousa, Christopher Stopford, Evelyn Hesse, Neil Davey & Yi Sun

  3. TIGP Bioinformatics Program, Academia Sinica, Taipei, 115, Taiwan

    Emmanuel Salawu

Authors
  1. Daniel Priori
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  2. Giseli de Sousa
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  3. Mauro Roisenberg
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  4. Christopher Stopford
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  5. Evelyn Hesse
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  6. Emmanuel Salawu
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  7. Neil Davey
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  8. Yi Sun
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Corresponding author

Correspondence to Daniel Priori .

Editor information

Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

  2. University of Lausanne, Lausanne, Switzerland

    Paolo Masulli

  3. Universitat Politécnica de Catalunya, Terrrassa, Spain

    Antonio Javier Pons Rivero

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Priori, D. et al. (2016). Using Machine Learning Techniques to Recover Prismatic Cirrus Ice Crystal Size from 2-Dimensional Light Scattering Patterns. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9887. Springer, Cham. https://doi.org/10.1007/978-3-319-44781-0_44

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  • DOI: https://doi.org/10.1007/978-3-319-44781-0_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44780-3

  • Online ISBN: 978-3-319-44781-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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