⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

January 1, 2026International Journal of Reliability and SafetyOpen Access

Hybrid SLnOdragonfly optimised CNN for enhanced prediction of injury severity in traffic accidents

Bijimol T.K.Amal M.R.Dileepkumar S. R Juby Mathew

View Full Paper

Ask AI

Bookmark

Share

Key Points

This research aims to improve the prediction of injury severity in traffic accidents using an optimized convolutional neural network (CNN).
Developed a hybrid SLnOdragonfly optimized CNN model.
Applied the model to data from traffic accidents for enhanced predictions.
Analyzed the performance based on accuracy metrics.
Achieved a significantly higher prediction accuracy compared to traditional models.
Showed improved outcomes in predicting severe injuries, enhancing decision-making in emergency responses.

Implication

Study predicts injury severity in traffic accidents, suggesting advanced machine learning techniques improve outcomes.

Abstract

No abstract yet. The journal hasn't published one we can show.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

T.K. et al. (2026) studied this question.

synapsesocial.com/papers/6a168b160c924ddd1bd59f2b https://doi.org/10.1504/ijrs.2026.10078758

View Full Paper

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Hybrid optimised deep learning model for detecting malicious nodes in mobile networkOriginal Research · 2026
2Enhancing intrusion detection system performance under imbalanced data conditions using a hybrid deep learning frameworkOriginal Research · 2026
3A hybrid machine learning approach for predicting traffic accident collision severityOriginal Research · 2026 · 1 citations
4A software fault prediction model using driving training-inspired metaheuristic feature selection frameworkOriginal Research · 2026
5Intelligent precision advertising via deep learning and multi-source data fusionOriginal Research · 2026

More related papers

Application of Hybrid AI Models in Supply Chain Recovery and Resilience Management2026
Enhancing heavy-duty natural gas engineperformance and emissions prediction with diffractive deep neural networks2025
Edge-Cloud Integrated Fraud Detection for E-Commerce Transactions Using Hybrid Siamese-LSTM Model2026

More from International Journal of Reliability and Safety

Rolling bearing fault vibration characteristic analysis software system accounting waviness and local defectsThu,
Climbing the Ladder Safely: Do R&D Spending and Economic Growth Influence Occupational SafetyThu,