Prediction of Flight Fare using Deep Learning Techniques

Due to the drastic growth in aviation sector, population living standard and adverse effect of the Covid-19 pandemic there is an increase in air travel in the recent years. However, Indian airline corporation use revenue management system to make real-time price adjustments, causing fare to fluctuate considerably. The price is characterized by considerable fluctuation, making it viable to conduct research on price prediction. This issue is addressed in this work where flight fare prediction is carried out by implementing deep neural network system. Furthermore, the attributes of the given dataset have been analyzed using various visualization technique such as correlation matrix, boxplot, bar chart and line plot. The results justify that the random forest and the gradient boos technique gives highest accuracy with the fare prediction dataset.