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Cognitive and Spatial Forecasting Model for Maritime Migratory Incidents: SIFM

Author

Listed:
  • Donatien Agbissoh Otote

    (Departamento de Ingeniería Topográfica y Cartografía ETSI Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid, 28031 Madrid, Spain)

  • Antonio Vázquez Hoehne

    (Departamento de Ingeniería Topográfica y Cartografía ETSI Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid, 28031 Madrid, Spain)

Abstract

The security challenges associated with maritime migratory incidents in the Mediterranean Sea since the onset of the 21st century are considerable. Reports of such incidents are generated almost daily, leading to significant scientific interest, including that of this manuscript. This article introduces a forecasting model specifically designed to equip maritime security stakeholders around the Mediterranean Sea with a technical instrument for estimating the frequency of maritime migratory incidents. The proposed model, the SIFM, encompasses five methodological steps: Tessellation: The initial step involves partitioning the maritime area affected by these incidents into distinct cells. Subsidiary process: In this phase, the cells are classified according to the year in which incidents were recorded. Containment index: This index quantifies the magnitude of incidents within the designated cells. Incidence growth index: This metric further refines the forecasting methodology. Maritime migration incident forecasting: The concluding step establishes a forecast interval for the anticipated quantity of maritime migratory incidents. This systematic approach aims to enhance the understanding and prediction of maritime migratory incidents within the Mediterranean region.

Suggested Citation

  • Donatien Agbissoh Otote & Antonio Vázquez Hoehne, 2025. "Cognitive and Spatial Forecasting Model for Maritime Migratory Incidents: SIFM," Forecasting, MDPI, vol. 7(2), pages 1-17, May.
    • Handle: RePEc:gam:jforec:v:7:y:2025:i:2:p:21-:d:1660288
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    References listed on IDEAS

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    2. Horneff, Wolfram J. & Maurer, Raimond H. & Stamos, Michael Z., 2008. "Life-cycle asset allocation with annuity markets," Journal of Economic Dynamics and Control, Elsevier, vol. 32(11), pages 3590-3612, November.
    3. Montero-Manso, Pablo & Athanasopoulos, George & Hyndman, Rob J. & Talagala, Thiyanga S., 2020. "FFORMA: Feature-based forecast model averaging," International Journal of Forecasting, Elsevier, vol. 36(1), pages 86-92.
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