{"title":"利用机器学习预测地震","authors":"Sachin Sawantt, Purva Golegaonkar, Prayas Gondane, Rushikesh Gole, Srushti Gole, Aniruddha Gondkar, Aditya Gorave, Rupali Deshpande","doi":"10.1051/itmconf/20235605017","DOIUrl":null,"url":null,"abstract":"One of the deadliest and riskiest natural disasters is an earthquake. They often occur without a warning or any further alert. Therefore there was a need for its prognosis as it is extremely important for mankind as well as the environment. In this project, the successful application of machine learning techniques have been used for different elements of research which would be possible to use to make a more accurate short-term prognosis of upcoming earthquakes. Random Forest Classifier is the algorithm used for the research.","PeriodicalId":433898,"journal":{"name":"ITM Web of Conferences","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Earthquake prognosis using machine learning\",\"authors\":\"Sachin Sawantt, Purva Golegaonkar, Prayas Gondane, Rushikesh Gole, Srushti Gole, Aniruddha Gondkar, Aditya Gorave, Rupali Deshpande\",\"doi\":\"10.1051/itmconf/20235605017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the deadliest and riskiest natural disasters is an earthquake. They often occur without a warning or any further alert. Therefore there was a need for its prognosis as it is extremely important for mankind as well as the environment. In this project, the successful application of machine learning techniques have been used for different elements of research which would be possible to use to make a more accurate short-term prognosis of upcoming earthquakes. Random Forest Classifier is the algorithm used for the research.\",\"PeriodicalId\":433898,\"journal\":{\"name\":\"ITM Web of Conferences\",\"volume\":\"4 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\":\"ITM Web of Conferences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1051/itmconf/20235605017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ITM Web of Conferences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1051/itmconf/20235605017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
One of the deadliest and riskiest natural disasters is an earthquake. They often occur without a warning or any further alert. Therefore there was a need for its prognosis as it is extremely important for mankind as well as the environment. In this project, the successful application of machine learning techniques have been used for different elements of research which would be possible to use to make a more accurate short-term prognosis of upcoming earthquakes. Random Forest Classifier is the algorithm used for the research.
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