Presently, airlines rely on expert systems to optimize their operations. Generally, these systems are created by experienced engineers. However, it’s difficult for these systems to incorporate all the different factors that may affect the optimal operating parameters. Because of this, we believe airlines would benefit from adding machine learning to their processes. For instance, Machine Learning would help airlines keep on top of emerging data trends. It can also help airlines recognize scheduling opportunities and risks.
Machine learning can incorporate a lot of data sources. It can also learn from past errors to predict if a flight will sell-out or not.
Machine learning can determine the objective function by learning from past inputs and revenue results. This leads to optimized flight planning and most importantly, maximum revenue.
Corrective AI can be used two ways to improve the overall effectiveness of an airline’s scheduling. Firstly, by predicting the probability of excess demand for each flight. Secondly, by optimizing the flight schedule to maximize revenue. Also, airlines can implement these strategies with a variety of data sources. (I.e. holidays and seasonal travel, weather patterns, etc). Altogether Corrective AI will enable an airline to increase average flight attendance and overall sold out flights. Airlines will also be able to avoid offering flight routes and times that would be unprofitable.
First, both parties tentatively agree on a proposed collaboration and sign a Mutual NDA.
Next, a 3-month Proof of Concept project is negotiated and initiated. Objectives to be outlined in a non-binding Letter of Intent.
Afterwards, PredictNow.ai researchers will conduct a proof of concept project to prove the effectiveness of the project.
Lastly, PredictNow.ai and the client sign a contract for a minimum of one year duration.
To inquire about starting a Proof of Concept with PredictNow.ai or if you have any questions, please fill out the contact form below and we’ll get back to you as soon as possible.