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Artificial Neural Network Based Empty Container Fleet Forecast

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Artificial Intelligence and Soft Computing (ICAISC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12854))

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Abstract

Global trade imbalances and poor, partial and unreliable information about available equipment make the coordination of empty containers a very challenging issue for shipping lines. The cancellation of transport operations once started or the extraordinary repositioning of containers are some of the problems faced by the local shipping agencies. In this paper, we selected the Artificial Neural Networks technique to predict the reception and withdrawal of empty containers in depots to forecast their future stock. To train the predictive models we used the different messages generated along the containers’ shipment journey together with the temporal data related to these events. The evaluation of the models with the test dataset confirmed the possibility of using ANN to predict the number of empty containers in depots.

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Author information

Authors and Affiliations

  1. R&D Projects, Fundacion Valenciaport, Valencia, Spain

    Joan Meseguer Llopis, Salvador Furio Prunonosa & Miguel Llop Chabrera

  2. Cosco Shipping Lines Spain, SA, Valencia, Spain

    Francisco J. Cubas Rodriguez

Authors
  1. Joan Meseguer Llopis
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  2. Salvador Furio Prunonosa
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  3. Miguel Llop Chabrera
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  4. Francisco J. Cubas Rodriguez
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Corresponding author

Correspondence to Joan Meseguer Llopis .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Meseguer Llopis, J., Furio Prunonosa, S., Llop Chabrera, M., Cubas Rodriguez, F.J. (2021). Artificial Neural Network Based Empty Container Fleet Forecast. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12854. Springer, Cham. https://doi.org/10.1007/978-3-030-87986-0_10

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  • DOI: https://doi.org/10.1007/978-3-030-87986-0_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87985-3

  • Online ISBN: 978-3-030-87986-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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