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 An Intelligent System to Forecast COVID-19 Pandemic using Hybrid Neural Network Subject The topic of the resource ARIMA; COVID-19; Forecasting; Hybrid; LSTM Description An account of the resource A current outbreak known as COVID-19 has been discovered from the coronavirus was informed by WHO. COVID-19 is a universal pandemic that has brought out the best and the worst of humanity. Due to an increase in the cases daily, COVID-19 is creating a menace to public health and establishes a disruption of the social and economic development of the countries. The problem is the hospitals are not able to provide proper facilities and treatments on time due to the lack of facilities in India. The purpose of this project to build an efficient hybrid deep learning model for forecasting the COVID-19 pandemic with multiple features that are responsible for the spread of COVID-19 in the top five states in India. In particular, a hybrid model that incorporates Auto-Regressive Integrated Moving Average and Long-term Short Memory is been used to forecast confirmed cases. The linear and non-linear dependencies in the dataset is been dealt with by an ARIMA-LSTM hybrid model. As a result, when compared to the outcomes of ARIMA, LSTM models independently, the hybrid model was giving better results and was performing well in forecasting COVID-19 cases. Through this, the policymakers will get prior information on COVID-19 cases in states which will help the government and healthcare departments to take prominent measures to prevent it. 2021 IEEE. Creator An entity primarily responsible for making the resource Vanahalli S.; Preethi N. Source A related resource from which the described resource is derived Proceedings - 2021 IEEE 10th International Conference on Communication Systems and Network Technologies, CSNT 2021, pp. 543-548. 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 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/CSNT51715.2021.9509622" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/CSNT51715.2021.9509622</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124700516&amp;doi=10.1109%2FCSNT51715.2021.9509622&amp;partnerID=40&amp;md5=91d682e8f876a444dfda65bf48705cad" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124700516&amp;doi=10.1109%2fCSNT51715.2021.9509622&amp;partnerID=40&amp;md5=91d682e8f876a444dfda65bf48705cad</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-073810523-9 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 Vanahalli S., Department of Data Science Christ (Deemed to be University), Lavasa, Pune, India; Preethi N., Department of Data Science Christ (Deemed to be University), Lavasa, Pune, India