A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering
Cluster methods such as k-means have been widely used to group areas with a relatively equal number of disasters to determine areas prone to natural disasters. Nevertheless, it is difficult to obtain a homogeneous clustering result of the k-means method because this method is sensitive to a random...
Main Authors: | Abdurrakhman Prasetyadi, Budi Nugroho, Adrin Tohari |
---|---|
Format: | Article |
Language: | English |
Published: |
UUM Press
2022-04-01
|
Series: | Journal of ICT |
Online Access: | https://e-journal.uum.edu.my/index.php/jict/article/view/15423 |
Similar Items
-
A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering
by: Prasetyadi, Abdurrakhman, et al.
Published: (2022) -
Identification of natural disaster impacted electricity load profiles with k means clustering algorithm
by: Jessen, Simon Hedegard, et al.
Published: (2022) -
A DATA ANALYSIS OF THE IMPACT OF NATURAL DISASTER USING K-MEANS CLUSTERING ALGORITHM
by: Prihandoko Prihandoko, et al.
Published: (2016-12-01) -
Identification of natural disaster impacted electricity load profiles with k means clustering algorithm
by: Simon Hedegård Jessen, et al.
Published: (2022-12-01) -
Integrated bisect K-means and firefly algorithm for hierarchical text clustering
by: Mohammed, Athraa Jasim, et al.
Published: (2016)