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 Deep Learning Advancements in E-commerce Supply Chain Management in Forecasting and Optimization Strategies Subject The topic of the resource Deep learning; E-commerce; Forecasting; Optimization; Supply chain management Description An account of the resource In this study, the influence of deep learning technologies on the optimization of supply chain management in the context of the e-commerce industry is examined. Using a dataset of historical data of sales, inventories, market fluctuations, and customer and supplier details, I investigate the efficiency of different deep learning models to predict demand and facilitate the optimal balance of inventories. Long Short-Term Memory (LSTM), Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), and a model proposed by the authors are defined and applied, considering their accuracy, precision, recall, and F-1 score. The results show that the proposed model outperforms traditional products, achieving 97.5% of accuracy. In the context of the comparative analysis, the specific features of CNN, LSTM, and RNN are revealed, helping to understand the benefits and drawbacks of each recommendation. As a result, the proposed model proves that deep learning technologies have the power to change the approach to predictive analytics and supply chain management, allowing practitioners to focus on strengths and overcome the weaknesses of their structures. The impact of data preprocessing and hyperparameters is also considered along with the necessity to choose the most appropriate model evaluation technique. In the future, it is possible to implement other complex deep learning models, integrate additional data, and address the problem of data scaling and heterogeneity. In the era of modern technologies, e-commerce organizations should take these findings into consideration to discover the potential of deep learning, improve supply chain performance, reduce costs, and attract clients. This research contributes to the topic of using deep learning technologies in supply chain management, promoting innovation, and changes that may affect the industry drastically. 2024 IEEE. Creator An entity primarily responsible for making the resource Singh J.; Shelke N.A.; Upreti K.; Saiyad F.B.J.; Divakaran P.; Madhukar K.S. Source A related resource from which the described resource is derived 2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation, SEFET 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/SEFET61574.2024.10718068" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/SEFET61574.2024.10718068</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208957887&amp;doi=10.1109%2FSEFET61574.2024.10718068&amp;partnerID=40&amp;md5=e94520d4e9964fc26326f684de1e1c40" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208957887&amp;doi=10.1109%2fSEFET61574.2024.10718068&amp;partnerID=40&amp;md5=e94520d4e9964fc26326f684de1e1c40</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038399-7 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 J., School of Computer Science Engineering &amp; Technology, Bennett University, Greater Noida, India; Shelke N.A., School of Computer Science Engineering &amp; Technology, Bennett University, Greater Noida, India; Upreti K., Christ (Deemed to be University), Department of Computer Science, Ghaziabad, India; Saiyad F.B.J., Bath spa university Rak, Department of Commerce, Ras Al-Khaimah, United Arab Emirates; Divakaran P., Himalayan University, Department of management, Itanagar, India; Madhukar K.S., KIT's Institute of Management, Education and Research, Kolhapur, India