 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: December 2025
Volume 10 | Issue 12
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19447
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | FLOOD AND LANDSLIDE PREDICTION USING MACHINE LEARNING |
| Authors Name: | Chaithra DN , Prof. Mohamed Rafi |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_205726
|
| Published Paper Id: | IJRTI2508071 |
| Published In: | Volume 10 Issue 8, August-2025 |
| DOI: | |
| Abstract: | Abstract Floods and landslides rank among the most devastating natural disasters, leading to widespread damage to lives, properties, and essential infrastructure worldwide. Timely and precise prediction of these disasters is essential for reducing their adverse impacts. Early and accurate prediction of such disasters is vital for minimizing their consequences. Yet, conventional forecasting methods often struggle due to the intricate and variable nature of environmental conditions. Recent advancements in machine learning (ML) offer promising solutions, employing sophisticated algorithms to manage these complexities. This paper presents an in-depth review of cutting-edge ML approaches for flood and landslide prediction, examining methodologies, datasets, advantages, and limitations. |
| Keywords: | Flood and Landslide Prediction, Machine learning, Risk analysis , Convolutional Neural Networks. |
| Cite Article: | "FLOOD AND LANDSLIDE PREDICTION USING MACHINE LEARNING", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 8, page no.a577-a589, August-2025, Available :http://www.ijrti.org/papers/IJRTI2508071.pdf |
| Downloads: | 000744 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2508071
Registration ID:205726
Published In: Volume 10 Issue 8, August-2025
DOI (Digital Object Identifier):
Page No: a577-a589 Country: Chikkamagaloru, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2508071 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2508071 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||