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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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) |
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| Paper Title: | Flood Prediction Using Machine Learning Model |
| Authors Name: | Sandhya Sandip Dhore , Devini Ramchandra Sable , Pallavi Manik Sakore , Jai Anil Shinde , Prof. K.S.Hangargi |
| Download E-Certificate: | Download |
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IJNRD_217040
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| Published Paper Id: | IJNRD2403656 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | Floods are among the most devastating natural disasters, causing extensive damage to both human lives and infrastructure worldwide. Timely and accurate flood prediction is crucial for mitigating the impacts of these events and enhancing community resilience. This abstract presents an overview of the current state of flood prediction, highlighting the growing importance of advanced forecasting models and data-driven approaches in improving prediction accuracy. Traditional flood prediction methods often rely on historical data and basic hydro logical models, which may not adequately capture the complexities of modern climate patterns and urbanisation. In recent years, advancements in technology, sensors, and computational power have revolutionised flood prediction by enabling the development of sophisticated predictive models. Integrating diverse datasets such as rainfall, river discharge, topography, land use, and weather forecasts to create a comprehensive model to predict flood rate. Leveraging machine learning and AI algorithms to process and analyse vast amounts of data, enabling the detection of patterns and trends that were previously challenging to identify flood endurance rate on basis of the output which is calculated using ultrasonic sensor. |
| Keywords: | Flood Prediction, Machine Learning, Sensor, Deep Learning |
| Cite Article: | "Flood Prediction Using Machine Learning Model", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.g457-g461, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403656.pdf |
| Downloads: | 00041 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2403656 Registration ID: 217040 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: g457-g461 Country: Pune, Maharashtra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403656 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403656 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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