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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Panwar, Dev Vishal | - |
dc.contributor.author | Seghal, Vivek Kumar [Guided by] | - |
dc.date.accessioned | 2023-09-13T04:34:33Z | - |
dc.date.available | 2023-09-13T04:34:33Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9966 | - |
dc.description | Enrollment No. 191520 | en_US |
dc.description.abstract | By analysing many environmental elements including precipitation, soil moisture, and terrain, landslide prediction using machine learning techniques is done. A predictive model was constructed that can accurately forecast the likelihood of landslides occurring in a particular area. The model can generalise well to new places because it was trained on historical landslip data and environmental parameters from many regions. The outcomes of our tests show that our model strongly predicts landslides and produces alerts. Our method has the potential to be employed as a landslip early warning system, lowering the danger of property damage and fatalities. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | Landslide | en_US |
dc.subject | Machine learning | en_US |
dc.title | Landslide Prediction using Machine Learning | en_US |
dc.type | Project Report | en_US |
Appears in Collections: | B.Tech. Project Reports |
Files in This Item:
File | Description | Size | Format | |
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Landslide prediction using Machine Learning by Dev Vishal Panwar.pdf | 1.78 MB | Adobe PDF | View/Open |
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