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 Book Chapter Book Chapter Faculty Publications- Book Chapter 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 The Evolution of Forecasting Techniques: Traditional Versus Machine Learning Methods Description An account of the resource Forecasting is used effectively and efficiently to support decision-making for the future. Over time, several methods have been created to conduct forecasting. Finding a forecasting technique with the ability to provide the best estimate of the system being modeled has always been a challenge. The selection and comparison criteria for forecasting methodologies can be organized in a variety of ways. Accurate forecasting has a great demand for various fields like weather prediction, economic condition, business forecasting, demand and supply forecasts and many more. When deciding whether to utilize a certain model to predict future events, accuracy is very important. In every field, machine learning (ML) algorithms are being used to forecast future events. These algorithms can handle more complex data and make predictions that are more accurate. Based on the least values of forecasting errors, forecasters create a model to determine the best strategy for prediction. For centuries, forecasting has been used to assist individuals in making future-related decisions. In the past, forecasts were based on intuition and experience, but as technology has advanced, so have forecasting methods. Currently, advanced ML models and methods for data analysis are used to provide forecasts. To forecast the future, these models incorporate a range of inputs, including historical data, present trends, and economic indicators. Forecasting is a vital tool for businesses to employ when making future plans. It is used in a wide range of industries, from finance to weather prediction. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. Creator An entity primarily responsible for making the resource Thomas A.; Johnson A.; Manoj M.J. Source A related resource from which the described resource is derived Artificial Intelligence in Forecasting: Tools and Techniques, pp. 73-90. Publisher An entity responsible for making the resource available CRC Press 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/10.1201/9781003399292-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003399292-5</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195946355&amp;doi=10.1201%2F9781003399292-5&amp;partnerID=40&amp;md5=e020aa549b8f0bc2edeafb89437cc071" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195946355&amp;doi=10.1201%2f9781003399292-5&amp;partnerID=40&amp;md5=e020aa549b8f0bc2edeafb89437cc071</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-104005150-4; 978-103250615-9 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 Book chapter 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 A., Department of Statistics and Data Science, CHRIST (Deemed to be University), Bengaluru, India; Johnson A., Department of Data Science, CHRIST (Deemed to be University), Pune, Lavasa, India; Manoj M.J., Department of Statistics and Data Science, CHRIST (Deemed to be University), Bengaluru, India