Authors : Harshita S; Swarnalatha

Volume/Issue : Volume 10 - 2025, Issue 8 - August

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DOI : https://doi.org/10.38124/ijisrt/25aug1482

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Abstract : This exploration presents a robust and interactive soothsaying system for force demand using Random Forest Regressor and Prophet model integrated into a stoner-friendly Streamlit- grounded web interface. The operation accepts force data with product-wise and date-wise deals, calculates net demand after counting for returns, expirations, and damages, and offers demand soothsaying and reduction simulations. crucial factors include an eco indicator for sustainability, rear logistics analysis, and amped demand visualizations. The model allows decision- makers to estimate unborn stock conditions, reduce waste, and optimize force chain effectiveness using real- time data analytics.

Keywords : Force Soothsaying, Streamlit, Random Forest, Prophet, Reverse Logistics, Eco Index, Supply Chain Optimization.

References :

1. Ramanathan, U.( 2012). Supply chain collaboration for bettered cast delicacy of promotional deals. International Journal of Operations & Production Management.
2. Hyndman, R.J., & Athanasopoulos, G. (2018). reading Principles and Practice, 2nd edition.  Texts.
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4. Zhang, D., Wang, Q., & Lai, K.K. (2017). Eco-efficiency in logistics A data net analysis approach. Journal of Cleaner Production.
5. Streamlit documentation- https// docs.streamlit.io
6. Scikit- learn Attestation- https//scikit-learn.org
7. Prophet- https// facebook.github.io/ prophet