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 Copper Price Prediction: A Machine Learning and Explainable AI Approach Subject The topic of the resource Copper price prediction; Explainable AI (XAI); Machine learning models; Random Forest algorithm; Time series forecasting Description An account of the resource This research introduces a hybrid model for copper price prediction, employs advanced machine learning models (linear regression, random forest, SVM, Adaboost, ARIMA), and utilizes the SHAP method for model interpretability. The study focuses on transportation-related variables over a 10-year period from Bloomberg Terminal, employing STL decomposition for time series forecasting. Key features impacting copper prices are identified, emphasizing the significance of demand, transportation, and supply. The Random Forest model highlights the critical role of demand. Addressing transportation supply constraints is crucial for enhancing model output in the dynamic copper market. 2024 IEEE. Creator An entity primarily responsible for making the resource Singh A.; Mahajan J.; Sharma M.; Saxena A.; Khan M.H.; Kakani R. 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/TQCEBT59414.2024.10545208" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT59414.2024.10545208</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204469793&amp;doi=10.1109%2FTQCEBT59414.2024.10545208&amp;partnerID=40&amp;md5=9386fa4b1f2ccb603876b8d2aa6b0550" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204469793&amp;doi=10.1109%2fTQCEBT59414.2024.10545208&amp;partnerID=40&amp;md5=9386fa4b1f2ccb603876b8d2aa6b0550</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 Singh A., Christ University, Bengaluru, India; Mahajan J., Christ University, Bengaluru, India; Sharma M., Christ University, Bengaluru, India; Saxena A., Christ University, Bengaluru, India; Khan M.H., Christ University, Bengaluru, India; Kakani R., Sg Analytics, India