Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Patnaik, Manorama; Kundu, Roumo; Bareen, Firdaus; Kundu, Tannisha; Raza, Shahid; Rawani, Rajesh Title A name given to the resource Advanced Machine Learning Framework for Precision Rainfall Prediction for Jharkhand, India Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived International Conference on Innovations in Intelligent Systems: Advancements in Computing, Communication, and Cybersecurity, ISAC3 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ISAC364032.2025.11156230" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ISAC364032.2025.11156230</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105018905342?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105018905342?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Patnaik M., Amity University Jharkhand, Amity Institute of Information Technology, Ranchi, India; Kundu R., ECT-Global VT India BLR, SAP Labs BLR, Bangalore, India; Bareen F., Amity University Jharkhand, Amity Institute of Information Technology, Ranchi, India; Kundu T., Amity University Jharkhand, Amity Institute of Information Technology, Ranchi, India; Raza S., Christ ((Deemed to Be) University, Department of Computer Science, Bangalore, India; Rawani R., Jharkhand Space Agency Centre, Ranchi, India Description An account of the resource Jharkhand, characterized by a substantial agricultural population predominantly reliant on rain-fed agriculture, faces significant challenges due to the erratic nature of precipitation. The study uses meteorological variables and historical rainfall data from the Jharkhand Space Agency Centre (JSAC) to predict rainfall with precision and resilience. Three supervised machine learning algorithms, Random Forest, K-Nearest Neighbour (KNN), and Ridge Regression, are employed to evaluate their performance across monsoon and non-monsoon periods. A novel algorithm is proposed for Jharkhand, offering better modularity and accuracy to predict the Rain Index. The results show the efficacy of these algorithms in capturing the temporal variability of rainfall in Jharkhand. The ensemble modeling model obtained an MSE score of 0.457, providing valuable insights into the viability and competence of machine learning algorithms for rainfall estimation. This research offers a valuable scope for policymakers, researchers, and stakeholders to formulate sustainable strategies to address climate variability and its impact on rain-fed agriculture. The study contributes significantly to meteorological research and offers valuable insights for policymakers, researchers, and stakeholders. 2025 IEEE. Subject The topic of the resource Crop Yield; Ensembled; Phase Expansion; Precipitation Index Prediction Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833153279-6; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online