An EWS for Prediction of Earthquake Using Deep Learning
Author(s):
Pooja K G, Manasa B , Pooja P , Vaibhavi V B, Sharan L Pais
Keywords:
Deep learning, Earthquake Early Warn- ing(EEW) system, Classification of hyperparameters, earthquake magnitude , CNN Algorithm .
Abstract
Earthquake Early Warning (EEW) system may be a period of time earthquake harm mitigation system. It detects, analyzes and transmits information of the next upcoming event at the potential user sites. An endeavor has been created to develop a multi-parameter-based EEW formula for correct and reliable supplying of EEW. The planned formula depends on a convolutional neural network (CNN) Algorithm that has the flexibility to extract vital options from waveforms that enabled the classifier to succeed in a strong performance within the needed earthquake parameters. Victimization of K-Mean formula to analyzing unstable datasets in conjunction with mental image for deciphering the results. With the advancement In machine learning and deep learning, it's attainable to extract helpful information and train models on massive datasets. we are able to predict the earthquakes supported that location’s knowledge and therefore the knowledge of larger area’s. Magnitude determination of earthquakes may be a obligatory step before An earthquake early warning (EEW) system sends an Alarm and therefore the foremost step includes classification of the Hyperparameters: location, magnitude, depth, and origin time of earthquake .
Article Details
Unique Paper ID: 156079

Publication Volume & Issue: Volume 9, Issue 2

Page(s): 786 - 791
Article Preview & Download


Share This Article

Conference Alert

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

Latest Publication

Go To Issue



Call For Paper

Volume 8 Issue 4

Last Date 25 September 2021

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies

Important Links

Browse Rsearch papers