Research Aim
Use AI and cloud computing together to improve ERP decision support, interpret module relationships, and support scalable enterprise operations.
Poster Summary
ERP modernization
BiLSTM-Attention
Cloud-native framing
AI and Cloud Computing in Business Systems
Poster-style summary of the published paper: A Hybrid Model for Enhancing Enterprise Resource Planning.
Core Metrics
91.2%
Accuracy with the proposed BiLSTM-Attention model, alongside 89.5% precision, 90.8% recall, and 90.1% F1-score.
Top Attention Insight
Module_5
Highest reported attention score: 0.17, suggesting the most influential role in ERP dependency prediction.
Modeling Pipeline
Architecture
What the model adds
- Bidirectional sequence context for module dependency learning.
- Attention-based interpretability for module influence analysis.
- Cloud ERP integration pathway for autoscaling, monitoring, and risk-aware orchestration.
Visual evidence
Module attention distribution
Precision vs recall
