BSP5 progress: Load Forecasting

Beginning of this year we started the development of the new BEONTRA suite with the current working title “BSP 5”. The overall goal is to create solution-based workflows and open up the existing modules to each other and the outside world. In addition, we are developing a user friendly and modern user interface which is combined with advanced machine learning intelligence to deliver a state-of-the-art product platform embracing the latest technology trends.

The first solution we are currently working on is “Load Forecasting”, i.e. the creation of loads (passengers, bags, fuel etc.) on the most recent schedules. With our machine learning algorithm significantly reducing the manual effort required, the Load Forecasting platform is the centerpiece to determine a flight-by-flight passenger forecast.

Load and schedule information can be analyzed in the flight event view

Currently, we are working on the first beta-version which will be made available to test users to try out the new machine learning algorithm and its predictions. The scope of the first version will be to publish the flight schedule in B Tactical, make it available within the new Load Forecasting platform, train the machine learning model with statistical data and do a flight-by-flight forecast for the total number of passengers. After the prediction is done, the data can be fed back into B Tactical to further work with it.

To validate our initial Machine Learning Algorithm, we started to compare the customer forecasts made within B Tactical with the Machine Learning results. Both were checked against the historical data. So far, we have analyzed 15 airports and focused on the following metrics. We were very happy to conclude that the target values have been achieved for all airports.

If you are interested in the results for your airport, please feel free to contact our Product Owner Kristin Wodzinski (wodzinski(at)beontra.com) and share your B Tactical scenarios and your historical data with her.