{"title":"Earthquake Location Forecasting In Map Using XGBOOST Algorithm","authors":"R. Jeena, Kruthika. .., P. A., Tanya. A.","doi":"10.54216/jchci.050104","DOIUrl":null,"url":null,"abstract":"Earthquake is one of the most threatening natural disasters which is caused due to the shaking of the earth’s surface. Common cause of earthquake is due to ground shaking, underground volcanic eruption. Here, XGBoost Algorithm is used to predict the location of the earthquake. In this paper, a earthquake location prediction method is proposed, which is based on the composition of a known system whose behaviour is administered according to the evaluation of more than two decades of seismic events and is designed as a time series using Machine learning. By analyzing the parameters such as Latitude, Magnitude, Depth, Longitude, Depth error, Gap, Time etc.","PeriodicalId":330535,"journal":{"name":"Journal of Cognitive Human-Computer Interaction","volume":"183 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognitive Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54216/jchci.050104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Earthquake is one of the most threatening natural disasters which is caused due to the shaking of the earth’s surface. Common cause of earthquake is due to ground shaking, underground volcanic eruption. Here, XGBoost Algorithm is used to predict the location of the earthquake. In this paper, a earthquake location prediction method is proposed, which is based on the composition of a known system whose behaviour is administered according to the evaluation of more than two decades of seismic events and is designed as a time series using Machine learning. By analyzing the parameters such as Latitude, Magnitude, Depth, Longitude, Depth error, Gap, Time etc.