I hereby declare that the work that is being presented by me in this project/study entitled “Japan Earthquake Hotspot Detection Using K-Means Clustering Method” is an authentic record of my own analysis and theoretical research carried out during the period from 1 st July 2022 to 31st August 2022 under the supervision of Mr. Anand Prakash, Scientist ‘D’. (Institute of Systems Studies and Analyses, Defence R&D Organisation, Ministry of Defence, Metcalfe House, Delhi 110054).
The aim of this study is to apply algorithm like K-mean Clustering algorithm on Japan Earthquake (2001-2018) Dataset to detect Hotspot which is in the field of 'Clustering' which is related to data mining, machine learning and lies under AI techniques.
Working of K-Means clustering Algorithm The following stages will help us understand how the K-Means clustering technique works- • Step 1: First, we need to provide the number of clusters, K, that need to be generated by this algorithm. • Step 2: Next, choose K data points at random and assign each to a cluster. Briefly, categorize the data based on the number of data points. • Step 3: The cluster centroids will now be computed. • Step 4: Iterate the steps below until we find the ideal centroid, which is the assigning of data points to clusters that do not vary. • 4.1 The sum of squared distances between data points and centroids would be calculated first. • 4.2 At this point, we need to allocate each data point to the cluster that is closest to the others (centroid). • 4.3 Finally, compute the centroids for the clusters by averaging all of the cluster’s data points. K-means implements the Expectation-Maximization strategy to solve the problem. The Expectation-step is used to assign data points to the nearest cluster, and the Maximization�step is used to compute the centroid of each cluster.
References
- https://www.analyticsvidhya.com/blog/2021/11/understanding-k-means-clustering-in-machine�learningwith-examples/
- https://www.kaggle.com/code/khotijahs1/k-means-clustering-of-iris-dataset
- https://towardsdatascience.com/a-practical-guide-on-k-means-clustering-ca3bef3c853d 26
- Dataset Source: https://www.kaggle.com/datasets/aerodinamicc/earthquakes-in�japan?resource=download&select=Japan+earthquakes+2001+-+2018.csv
- https://stackabuse.com/k-means-clustering-with-scikit-learn/
- https://rpubs.com/AnanyaDu/361293#:~:text=Iris%20Dataset%20%2D%20Clustering%20using%20K %20means&text=The%20data%20gives%20the%20measurements,to%20cluster%20them%20into%2 0groups.
- https://www.japan-guide.com/e/e2116.html
- http://eprints.lse.ac.uk/62495/1/Hunter_Earthquakes%20in%20Japan.pdf