Publikasi Ilmiah STMIK Banjarbaru
metadata only
Prediksi Safety Stock Menggunakan Algoritma Support Vector Regression Dengan Optimasi Hyperparameter
Inventory management plays an essential role in ensuring smooth supply chain operations and preventing both stockouts and overstocking. One effective approach to determining the appropriate level of safety stock is the use of machine learning–based prediction methods. This study aims to predict safe
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Safety stock calculation with heteroscedastic, autocorrelated and heavy-tailed forecast errors, an adaptive parametric method.e#1354512
- Managing Trade-offs in Food Systems: How holistic risk assessment can support better policy decisions#395419
- Enhancing financial stability in healthcare through data-driven risk assessments with machine learning.#214293
- Crop Yield Prediction using Random Forest Algorithm#104413
- Food security and agricultural challenges in West-African rural communities: a machine learning analysis#328772
Record · ID 1226318
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive