Conceptio › Archive › REPOSITORIO INSTITUCIONAL DA UFOP
REPOSITORIO INSTITUCIONAL DA UFOP metadata only

Predicting resilient modulus for pavement design : a comprehensive review of artificial neural network applications.

Silva, Bruno Oliveira da et al.
REPOSITORIO INSTITUCIONAL DA UFOP · Papers
Open Source ↗
artificial-neural-networks
The Resilient Modulus (MR) is an essential parameter describing the mechanical behaviour of pavement materials, but the tests to obtain it are time-consuming and costly. Therefore, machine learning, especially Artificial Neural Networks (ANN), has recently been an effective alternative for predictin
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

Record · ID 1135643
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