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 'Enhancing Electricity Price Forecasting': Integrating Macro-Economic Factors And Renewable Energy Dynamics in A Machine Learning Approach Subject The topic of the resource AdaBoost; ARIMA; Electricity price forecasting; Machine learning; Random Forests Description An account of the resource In the ever-evolving electricity market, accurate price prediction is imperative for informed decision-making. This research introduces an innovative predictive model that integrates renewable energy, macro-economic indicators, and external factors to enhance forecasting accuracy. By exploring historical trends, comparing machine learning algorithms, and employing advanced feature selection methods, the study addresses the complexities of the electricity market, emphasizing economic indicators, geopolitical events, and demand-supply dynamics. Informed by a literature review, the research underscores the necessity of dynamic models in electricity price forecasting. Utilizing machine learning models such as linear regression, random forest, SVM, AdaBoost, and ARIMA, the study aims to improve prediction accuracy. With a robust methodology and comprehensive evaluation metrics (MAE, RMSE, MAPE), the research contributes valuable insights into electricity market dynamics, providing a variable dictionary for clarity and emphasizing the strategic implications of the superior random forest model for stakeholders in the electricity sector. 2024 IEEE. Creator An entity primarily responsible for making the resource Duke R.; Mahajan J.; Rakesh K.; Khan M.H.; Sharma M.; Saxena A. Source A related resource from which the described resource is derived TQCEBT 2024 - 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 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/TQCEBT59414.2024.10545259" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545259</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204455591&amp;doi=10.1109%2FTQCEBT59414.2024.10545259&amp;partnerID=40&amp;md5=e903202212de953846ff5046300bed0e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204455591&amp;doi=10.1109%2fTQCEBT59414.2024.10545259&amp;partnerID=40&amp;md5=e903202212de953846ff5046300bed0e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038427-7 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 Duke R., Christ University, Bengaluru, India; Mahajan J., Christ University, Bengaluru, India; Rakesh K., Sg Analytics, India; Khan M.H., Christ University, Bengaluru, India; Sharma M., Christ University, Bengaluru, India; Saxena A., Christ University, Bengaluru, India