Ticket booking system to attain faster transaction using swarm intelligence technique comparing over Adaboost algorithm.

The primary objective of the project is to develop a method for achieving speedier transactions in an online railway ticket booking system by using an algorithm that is based on machine learning classifiers. The author of this study focused on analysing two distinct categories: the Swarm Intelligence Technique and the Adaboost Algorithm. The algorithms have been implemented and evaluated using data from a dataset that has 9,000 records. Through the use of the programming experiment, we have carried out N=10 iterations on each method, testing it with a variety of parameters in order to get a satisfactory accuracy %. In this study, the Swarm Intelligence Technique was used to improve the efficiency of the railway ticket booking system, which resulted in speedier transactions and an accuracy rate that was 96 percent higher than the previous system. The Swarm Intelligence Technique is more accurate than the Meta Heuristic Algorithm, and its significance value of 0.015, which is lower than 0.05, indicates that the hypothesis is more accurate. [ABSTRACT FROM AUTHOR]