Earthquakes in Turkey Situation, Linear Regression and Clustering Using K-Mean Algorithm

EasyChair Preprint 8371

Abstract

Unlike other natural disasters, earthquakes happen so frequent, this makes them most terrifying, and precautions would have to made in every aspect of human’s lives, constructions, business and individual. Earthquake’s prediction has been every geologist, scientists and mathematicians target for centuries. The goal of this research is to cluster Turkish cities using k mean algorithm. Linear regression was used to extrapolate the seismic activity in Turkey. This preliminary research cover also a descriptive part of earthquakes in Turkey. The dataset used is owned by Bogazici University and the analysis was conducted using Tableau public. We identified that earthquake count case clustering showed better accuracy than maximum magnitude case clustering, also linear regression line equation and chart predicted that the earthquake counts in Turkey is expected to increase by 11% in the next 10 years.

Keyphrases: Clustering, Earthquakes, K-mean algorithm, linear regression

@booklet{EasyChair:8371,
  author    = {Hunaida Avvad and Yousef Al Barjakly},
  title     = {Earthquakes in Turkey Situation, Linear Regression and Clustering Using K-Mean Algorithm},
  howpublished = {EasyChair Preprint 8371},
  year      = {EasyChair, 2022}}