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Rainfall Forecast using an Effective Machine Learning Model

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Rainfall Forecast using an Effective Machine Learning Model


Numan Khan | Shubham Kumar



Numan Khan | Shubham Kumar "Rainfall Forecast using an Effective Machine Learning Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-3, June 2025, pp.436-441, URL: https://www.ijtsrd.com/papers/ijtsrd79960.pdf

Interfacing with the ever-increasing volumes of data in the sectors of technology, medicine, science, engineering, industry, and finance and transforming them into a comprehensible format. One of the primary criteria is a human user. Information-intensive applications will demand effective methods and the ability to learn from fresh data in order to swiftly identify and evaluate intricate patterns and requirements. Classification and clustering of widely accessible data is one way to address this. Within this research, we suggested a two -tier method for clustering big data sets for rain fall data prediction using SOM and SVM with ID3 in order to partially satisfy the market demand. This research examines a novel method for grouping the SOM and SVM with ID3. Specifically, application of agglomerative hierarchical clustering and ID3-participated clustering is examined. When compared to straight clustering of the data, the two-stage process, which first uses SOM to create the illustration and then examines SVM with ID3, performs well and cuts down on computation time.

Rainfall prediction, SOM, SVM, ID3, ANN, Clustering, Forecasting, Entropy, Data mining, Weather data


IJTSRD79960
Volume-9 | Issue-3, June 2025
436-441
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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