Publication2025
A Hybrid GRU-DQN Framework for Real-Time Traffic Prediction and Adaptive Signal Control in Smart Cities
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- Proceedings of IEEE International Conference on Emerging Engineering Technologies and Applications IC Eeta 2025
- Pages
- 740-747
- Published
- 1 January 2025
- DOI
- 10.1109/ic-eeta66496.2025.11548004
- Scopus ID
- 105042657250
- Authors
- 5
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
11 Make cities and human settlements inclusive, safe, resilient and sustainable
GRU-DQN framework for smart city traffic prediction and adaptive signal control reduces queue length and improves throughput
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.4 Infrastructure and connectivity
Smart city infrastructure technology optimizes urban traffic management with machine learning-based intelligent control systems
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
Evidence
Kortex hosts no documents. Evidence is an outbound link to the authority that holds it.
No outbound evidence link is recorded for this activity. The record below states which source it came from and when it was last read.
Provenance
Which source system this record came from, how many source rows were resolved into it, and when each was last read.
- Source rows resolved into this record
- 1
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
This URL is stable. A record’s permalink is frozen when it is published and is not regenerated if its title is later corrected.
KIIT Deemed to be University. “A Hybrid GRU-DQN Framework for Real-Time Traffic Prediction and Adaptive Signal Control in Smart Cities”. Kortex.