Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Vol 3, No 3, August 2018

Application Kohonen Network and Fuzzy C Means for Clustering Airports Based on Frequency of Flight

Rahmalia, Dinita (Unknown)
Herlambang, Teguh (Unknown)

Article Info

Publish Date
16 Apr 2018

Abstract

In Indonesia, the demands of air tranportation for reaching destination increase rapidly. Based on the flight schedule in airports spreading in Indonesia, the airports have different flight demand rate so that it requires clustering. This research will use two methods for clustering : kohonen network and Fuzzy C Means (FCM).Kohonen network is the type neural network which uses unsupervised training.Kohonen network uses weight vectors for training while FCM uses degree of membership. Both kohonen network and FCM, inputs are represented by the number of departure and arrival of airline in one day. For kohonen network, we update weight matrices so that minimizing the sum of optimum euclidean distance. For FCM, we update degrees of membership so that minimizing the objective function value.From the simulations, we can cluster the airports based on the number of departure and arrival of airline.

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Journal Info
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Website

Abbrev

kinetik

Publisher

Universitas Muhammadiyah Malang

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Description

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control was published by Universitas Muhammadiyah Malang. journal is open access journal in the field of Informatics and Electrical Engineering. This journal is available for researchers who want to improve ...