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 Comparative Analysis of CPI prediction for India using Statistical methods and Neural Networks Subject The topic of the resource ARIMA; Consumer Price Index; GRU; Holt-Winters; LSTM; RNN; SARIMA; Stacked LSTM Description An account of the resource Inflation is one of the main issues affecting the world economy right now, necessitating the accurate inflation prediction for the development of tools and policies by the monetary authorities to prevent extreme price volatility. Expectations of inflation influence many financial and economic actions, and this dependence motivates economists to develop techniques for precise inflation forecasting. Nearly everyone in the economy is impacted by inflation, including lending institutions, stock brokers, and corporate financial officials. In many cases, inflation determines whether a firm will accept a particular project or if banks will make a particular loan. These different economic actors can modify their financial portfolios, strategic goals, and upcoming investments if they are able to forecast changes in inflation rates. The multiple interaction economic components that depend on inflation will be better understood by economic agents operating in a business context if inflation forecasting accuracy is improved. There are numerous techniques to forecast inflation ranging from basic statistical methods to complex neural network methods. Therefore, this paper employs LSTM model to train and analyze the Consumer Price Index (CPI) indicators to obtain inflation-related prediction results. The experimental results on historical data show that the statistical model has good performance in predicting India's inflation rate compared to deep learning methods in case of smaller dataset. 2023 IEEE. Creator An entity primarily responsible for making the resource Singh A.; Shukla B.; Jos J. Source A related resource from which the described resource is derived 2023 2nd International Conference for Innovation in Technology, INOCON 2023 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 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/INOCON57975.2023.10101073" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/INOCON57975.2023.10101073</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158028795&amp;doi=10.1109%2FINOCON57975.2023.10101073&amp;partnerID=40&amp;md5=af2acde42f28062b99ddbb6361718b71" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85158028795&amp;doi=10.1109%2fINOCON57975.2023.10101073&amp;partnerID=40&amp;md5=af2acde42f28062b99ddbb6361718b71</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835032092-3 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 Singh A., Christ (Deemed to Be University), Dept. of Data Science, Pune, India; Shukla B., Christ (Deemed to Be University), Dept. of Data Science, Pune, India; Jos J., Christ (Deemed to Be University), Dept. of Data Science, Pune, India