Lume 5.8
metadata only
Modeling of asphalt-rubber rotational viscosity by statistical analysis and neural networks
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
- A comparison of Statistical and Neural Network models in volatility modeling#284096
- Rheological study of asphalt binders with a wax-based Warm Mix Additive and its relationships to mix compaction and rutting#957872
- Aptula, A.O.; Jeliazkova, N.G.; Schultz, T.W.; Cronin, M.T.D. The Better Predictive Model: High q2 for the Training Set or Low Root Mean Square Error of Prediction for the Test Set?. QSAR Comb. Sci. 2005, 24, 3, 385–396.#933210
- Inverse design of cement and cement paste composition for targeted tensile strength using sequential neural networks and hydration based micromechanical modelling#670211
- IMPACT OF ASPHALT BINDER CHEMICAL COMPOSITION ON THE PERFORMANCE OF ASPHALT MIXTURE.#823339
Record · ID 630659
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