Pubblicato su stage4eu il: 24/04/2019 Ortec, Graduation Project: Developing A Machine-Learning Based Attribute Prediction Model

Ortec
Houtsingel 5, Zoetermeer, Paesi Bassi
Informatica/ICT, Engineering, Statistica/Data analysis
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Attività:

The positioning of a container on the yard plays a crucial role in efficient terminal operations. To optimize the positioning of a container on the terminal, certain data is needed. Destination, dwell time and mode of next transport are essential attributes when determining the position of the container, however usually not yet known when the container has to be assigned to a location. By combining historical data with attributes that are known, we can predict an expected value for the unknown attributes of an incoming container, thereby enhancing the positioning of this container on the yard. We call the process of predicting these unknown attributes ‘container profiling’.

This thesis is about container profiling, one of the essential elements to get the positioning on the terminal right. Using a set of historical data, we expect we can predict attributes of newly arriving containers. Your assignment will be to create and train this model. Deliverables & expectations:

  • A thesis on the theoretical framework and issues found
  • A functioning model trained to work with diverse datasets of containers
  • Basic logic on using the container profile within the yard
  • Proposed next steps for further research
  • Active collaboration in the LAB environment.
Requisiti principali:
  • You are a student in the master’s phase of your course in the area of Econometrics, Mathematics, Computer Science, Business Informatics, Information Science or comparable
  • You can handle a high degree of complexity and work in a team
  • You are enthusiastic about the port-related industry
  • You possess skills in coding algorithms; experience with machine learning is considered an asset
  • Able to fluently communicate in English (verbally and in writing).