Using AI And Machine Learning Efficiently To Decide On Voyage Fixture Of Tanker Ships To Increase Turnarounds And Profitability

Authors

  • Sathya Narayan Balaji SSBM, Geneva
  • Dr. Mario Silic Swiss School of Bussiness & Management, Geneva

Keywords:

Artificial Intelligence, Machine Learning, Merchant Shipping, Oil tankers, Ship Chartering, N.L.P

Abstract

This research paper brings insights on how Artificial Intelligence and Machine Learning principles can be leveraged to predict the shipping ports turnaround patterns with prime focus on the Tanker shipping markets and associated factors which will be used to analyze the market trends in order to improve the turnaround timings of the vessel and inturn result in the Profitability. Natural Language Processing (N.L.P), data processing to extract insights from the test data will also be explored as a part of this research.

Author Biography

Dr. Mario Silic, Swiss School of Bussiness & Management, Geneva

https://www.researchgate.net/profile/Mario-Silic

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Published

2022-04-13

How to Cite

Balaji, S. N., & Silic, M. (2022). Using AI And Machine Learning Efficiently To Decide On Voyage Fixture Of Tanker Ships To Increase Turnarounds And Profitability. Global Journal of Business and Integral Security, 1(1). Retrieved from https://gbis.ch/index.php/gbis/article/view/63

Issue

Vol. 1 No. 1 (2022)

Section

Articles