Advanced Delivery Time Prediction System Using Machine  Learning and Real-time Data Integration

Aishwarya S. Pathak,Pramod G. Rahate ,Neeraj A. Gangurde ,Megha A. Patil,Urvashi T. Bhat,Shruti H Gunjotikar

Advanced Delivery Time Prediction System Using Machine Learning and Real-time Data Integration

Authors

Aishwarya S. Pathak,Pramod G. Rahate ,Neeraj A. Gangurde ,Megha A. Patil,Urvashi T. Bhat,Shruti H Gunjotikar

Keywords:

Machine Learning, Delivery Time Prediction, CatBoost, Real-time Data Integration

Abstract

Accurate delivery time prediction has become crucial in today's e-commerce and logistics environment. Traditional methods often
fail to account for real-time factors, leading to customer dissatisfaction and operational inefficiencies.

References

Wolter, J., & Hanne, T. (2024). Prediction of service time for home delivery services using machine learning. Soft Computing, 28, 5045–5056.

Xu, Z., Yuan, J., Yu, L., Wang, G., & Zhu, M. (2024).

Machine learning-based traffic flow prediction and intelligent traffic management. International Journal of Computer Science and

Information Technology, 2(1).

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Published

2024-12-01

How to Cite

Aishwarya S. Pathak,Pramod G. Rahate ,Neeraj A. Gangurde ,Megha A. Patil,Urvashi T. Bhat,Shruti H Gunjotikar. (2024). Advanced Delivery Time Prediction System Using Machine Learning and Real-time Data Integration . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 2425–2430. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2111