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 Conference Papers 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/. Title A name given to the resource ThermAI: Exploring Temperature Analysis Through Diverse Machine Learning Models Subject The topic of the resource Machine learning methods; Meteorological forecasting; Random forests; Temperature predictions Description An account of the resource Meteorological forecasting is crucial in multiple industries, including agriculture, aviation, and daily routines. The objective of this inquiry is to improve temperature predictions by examining and comparing several machine learning methods, such as linear regression, decision trees, and random forests. This work aims to fill the gap in assessing machine learning models for temperature forecasting on a broader scale by utilising the comprehensive Indian meteorological dataset, which covers a wide range of geographical regions. The research utilises a thorough technique that includes gathering data, selecting relevant features, choosing appropriate models, and evaluating the results using R-squared and Mean Square Error metrics. The findings demonstrate that the Random Forest model surpasses both multiple linear regression and decision trees in terms of performance, displaying superior accuracy and reduced prediction errors. This study enhances proactive weather management and decision-making processes by offering valuable insights and tools to stakeholders in various industries. The work is organised into distinct sections that encompass a literature review, methodology, results, and conclusions, providing a comprehensive viewpoint on developments in temperature forecasting. 2024 IEEE. Creator An entity primarily responsible for making the resource Thomas D.R.B.; Joy H.K. Source A related resource from which the described resource is derived 1st International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICECCC61767.2024.10593875" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICECCC61767.2024.10593875</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200676343&amp;doi=10.1109%2FICECCC61767.2024.10593875&amp;partnerID=40&amp;md5=f800e9b2b92ef9f1d9ee6fc790fc086a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200676343&amp;doi=10.1109%2fICECCC61767.2024.10593875&amp;partnerID=40&amp;md5=f800e9b2b92ef9f1d9ee6fc790fc086a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835037180-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Thomas D.R.B., CHRIST University, Department of computer science, Bangaluru, India; Joy H.K., CHRIST University, Department of computer science, Bangaluru, India