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From "Janardhan (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SYSTEMML-1784) Predict Earthquakes and their magnitudes.
Date Fri, 26 Jan 2018 14:27:00 GMT

    [ https://issues.apache.org/jira/browse/SYSTEMML-1784?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16341107#comment-16341107
] 

Janardhan commented on SYSTEMML-1784:
-------------------------------------

This is for keep tracking my issues for running the scripts in distributed fashion. It will
take 3 more months to work on.

This project is not open source, so only the improvements & scaling of the scripts will
be addressed here, but not the script itself. Thanks.

 

> Predict Earthquakes and their magnitudes.
> -----------------------------------------
>
>                 Key: SYSTEMML-1784
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1784
>             Project: SystemML
>          Issue Type: Epic
>          Components: Algorithms
>            Reporter: Janardhan
>            Assignee: Janardhan
>            Priority: Major
>         Attachments: Earthquakes magnitude predication using artificial neural network
in northern Red Sea area..pdf
>
>
> h3. Predicting Earthquakes with Apache SystemML.
> _{color:#707070}Earthquakes take a dreadful human toll. Some 10,000 people die each year
in earthquakes and their aftermath, but the toll can be much higher. Over 230,000 people died
in the tsunami that followed the magnitude 9 quake off the coast of Sumatra in 2004; more
than 200,000 died in Haiti in 2010 after the country was hit by a magnitude 7 quake; and more
than 800,000 are thought to have died in a quake in China in 1556.^1^{color}_
> So a better way—any way—to forecast quakes would be hugely valuable.
> With the recent advancements in research in the fields and after some successful predictions,
we strongly believe that it is possible to predict an earthquake.
> References:
> 1. https://www.technologyreview.com/s/603785/machine-learning-algorithm-predicts-laboratory-earthquakes/
> Goal & Approach:
> 1. dx.doi.org/10.1016/j.jksus.2011.05.002
> 2. https://arxiv.org/ftp/arxiv/papers/1702/1702.05774.pdf



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