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© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM19027

MACHINE LEARNING PROJECT ON EARTHQUAKE PREDICTION SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM19027

Volume:

7 |

4 |

Apr 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AK

Amit Kumar

MG

Manas Gupta

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Abstract

In current situation, an explicit forecaster is planned and created, a framework that may conjecture the disaster. It centres around distinguishing early indications of Earthquake by utilizing AI calculations. Framework is qualified for essential strides of making learning frameworks alongside life pattern of data science. Informational indexes for Indian sub-mainland alongside remainder of the globe are gathered from government sources. Pre-handling of data is trailed by development of stacking model that joins Random Forest and Support Vector Machine Algorithms. This mathematicalmodel is formed using algorithms hooked in to “training data- set”. Model searches for design that prompts fiasco and go with it in its structure, to create decisions and gauges without being explicitly modified to play out the assignment. After figure, we broadcast the message to government authorities and across different stages. Time, Locality and Magnitude, these 3 factors addresses the focus of information acutely.

KEYWORDS

SVM Random Forest training data-set.

Cite This Article

Amit Kumar, Manas Gupta, "MACHINE LEARNING PROJECT ON EARTHQUAKE PREDICTION SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 4, Apr 2023. https://doi.org/10.55041/IJSREM19027

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Publication Date

4/17/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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