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DavieObi/Demand-Forecasting-and-Inventory-Optimization

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This project applies time series forecasting (ARIMA) to predict product demand and optimize inventory management. By analyzing historical demand and stock levels, it calculates reorder points, safety stock, and optimal order quantities to minimize costs, prevent stockouts, and improve service efficiency.

active 2025-07-30 → 2026-02-10 (UTC)

Complete coverage27,988 / 27,988 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-24 (UTC)
Events
45
Pushes
1
Pull requests
0
Issues
0
Stars
24
Forks
19

Activity over time

Daily event counts in the loaded window

Line chart, 196 days from 2025-07-30 to 2026-02-10. Pushes: 1 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 24 total, peak 11 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
DavieObi1100

Recent activity

Latest issues, pull requests and releases

No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 24 stars here means stars gained during the window, not the repo's star count.