L2M-Shipping rate forecasting using deep learning solutions

In the complex and ever-evolving realm of shipping investments and operations, informed decision-making stands
as a cornerstone of success. Within Soshianest Inc., the primary focus lies in providing precise and reliable
freight rate forecasts. Through the utilization of state-of-the-art AI models, the company aims to enhance
shipping strategies, enable data-driven decision-making, and adeptly maneuver through market variations with
assurance .

Our objective is to implement advanced Time Series Forecasting (TSF) methodologies to forecast shipping rates
within the dynamic shipping markets. Leveraging historical shipping feature datasets and supplementary
resources such as up-to-date economic news, our goal is to meticulously analyze the historical trends and
harness generative AI techniques to achieve precise and reliable predictions of shipping freight rates.

A critical gap in our project lies in the limited interaction with individuals employed in maritime-related enterprises.
This absence necessitates the formulation of various assumptions to address issues such as missing data.
Leveraging this invaluable wellspring of firsthand experience, rooted in human interactions with the available
data, has the potential to introduce significant value and enhancements to the framework’s design.

Faculty Supervisor:

Fayez Gebali

Student:

Partner:

I-INC Foundation for Business Development

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Victoria

Program: