OpenAIRE
metadata only
Machine learning to enhance the management of highway pavements and bridges
The adoption of machine learning in transportation asset management is hindered by the perception of it being a black box, the natural resistance to change and the challenges of integration with existing management systems. This paper aims to enhance the understanding of machine learning and provide
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
- Machine learning and AI model for encroachment and change detection — Punjab Urban Land Systems Enhancement Project (Pakistan)#606605
- Machine learning models in an artificial intelligence infrastructure — Pure Storage, Inc. (US12373428B2)#607044
- A Systematic Review of Context-Aware Artificial Intelligence and Machine Learning Approaches for Road Risk Prediction#126966
- A Systematic Review of Context-Aware Artificial Intelligence and Machine Learning Approaches for Road Risk Prediction#126965
- Urban Artificial Intelligence in Mobility Infrastructure: Lessons for Just and Inclusive Cities#90495
Record · ID 1427196
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