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 Exploring Advances in Machine Learning and Deep Learning for Anticipating Air Quality Index and Forecasting Ambient Air Pollutants: A Comprehensive Review with Trend Analysis Subject The topic of the resource air pollutants; AQI; Artificial Neural Network; Linear Regression; Prediction Description An account of the resource India and the rest of the world are growing more and more worried about polluted atmosphere on a daily basis. A comprehensive prevision and prognostication of air quality parameters is vital due to the major harm that air pollution causes to both the environment and public health, causing concern on a global scale. In-depth analyses of the methods for predicting ambient air pollutants, like carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter with diameters less than 10? (PM10) and less than 2.5? (PM2.5), and ozone (O3), are provided in this work in tandem with the modeling of the Air Quality Index (AQI).To further enhance the anticipated precision and applicability of these models, the assessment additionally employs trend analysis to determine precedents and new trends in air quality. This paper offers insights into recent advances in algorithms using deep learning and machine learning for anticipating AQI and forecasting pollutant concentrations by combining current research in this topic. In order to inform policy decisions and measures aimed at reducing air pollution and its adverse effects on public health, trend analysis integration affords a more thorough comprehension of the dynamics of air quality. 2024 IEEE. Creator An entity primarily responsible for making the resource Rajan D.; Rohini V. Source A related resource from which the described resource is derived 2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 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/ICCCNT61001.2024.10725099" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCCNT61001.2024.10725099</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211171976&amp;doi=10.1109%2FICCCNT61001.2024.10725099&amp;partnerID=40&amp;md5=81e37958607ee4de99469b0352c11b14" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211171976&amp;doi=10.1109%2fICCCNT61001.2024.10725099&amp;partnerID=40&amp;md5=81e37958607ee4de99469b0352c11b14</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835037024-9 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 Rajan D., Christ (Deemed to be University), Department of computer science, Bangalore, India, Cmr Institute of Technology, Department of Mca, Bangalore, India; Rohini V., Christ (Deemed to be University), Department of computer science, Bangalore, India