Airline Traffic Analysis Using Clustering Method in R Language

S. Thanganila; T. Keerthana; P. Tamilzhchelvi

doi:10.51983/ajcst-2019.8.S2.2036

Authors

S. Thanganila PG Student, Department of Computer Science, Ayya Nadar Janaki Ammal College, Sivakasi, Tamil Nadu, India
T. Keerthana PG Student, Department of Computer Science, Ayya Nadar Janaki Ammal College, Sivakasi, Tamil Nadu, India
P. Tamilzhchelvi Associate Professor, Department of Computer Science, Ayya Nadar Janaki Ammal College, Sivakasi, Tamil Nadu, India

DOI:

https://doi.org/10.51983/ajcst-2019.8.S2.2036

Keywords:

Cluster Analysis, Airline Data, K-Means Algorithm, Google Cloud

Abstract

In this paper, we analyze the airlines traffic in R using k-means clustering algorithm to avoid traffic in airlines. Clustering is the process of grouping data, where grouping is recognized by discovering similarities between data based on their features. K-Means algorithm is applied to get results and to predict before any problem arise in airline traffic. R takes too much time to load huge amount of data and sometimes does not support to upload huge volume of datasets. So, to avoid this space and time complexity, we have used Google Cloud.

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