Presentation Details
Dynamic NeuroFusion Ensemble Prediction System for Retail Sales and Customer Behaviour Prediction
ID：76
View Protection：ATTENDEE
Updated Time：2026-07-22 16:09:42 Hits：10
In-person
Start Time：2026-07-31 12:25（Asia/Kolkata）
Duration：15min
Session：S6 Artificial Intelligence Use Cases »
No files
Abstract
Abstract—The increasing complexity of retail operations and evolving market patterns has created a significant need for intelligent prediction models that support data-driven decision-making. However, conventional Machine Learning (ML) and Deep Learning (DL) models often encounter difficulties in handling heterogeneous retail data, nonlinear feature relationships, redundant variables and complex predictive patterns. This research proposes a Dynamic NeuroFusion Ensemble Prediction System (DNEPS) for retail product-demand classification. DNEPS incorporates a NeuroWeave Feature Intelligence Layer (NFIL) for adaptive feature-interaction learning, an Adaptive Performance-Guided Ensemble Layer (APGEL) for assigning validation-based weights to individual learners and an Intelligent Fusion and Decision Layer for generating integrated predictive insights. The framework combines Random Forest, XGBoost, LightGBM and Deep Neural Network (DNN) models within unified ensemble architecture. The proposed system was evaluated using a large-scale synthetic Retail Sales and Customer Behaviour Analysis dataset, with product demand categorized into low, medium and high-demand classes. Leakage-free preprocessing and training-derived percentile thresholds were used during model development. Experimental results indicate that DNEPS achieves 98.6% accuracy, outperforming the selected baseline models. These findings demonstrate the effectiveness of adaptive feature intelligence and performance-guided ensemble fusion for reliable retail demand classification and decision support.
Keywords
Keywords—Adaptive Ensemble Learning, Decision Intelligence, NeuroWeave Feature Intelligence, Organizational Forecasting, Predictive Analytics, Retail Analytics
Speaker
Dr Agila G
Professor Sri Ramakrishna College of Arts & ScienceSubmission Author
All Comments
Important Date
-
Conference Date
Jul 30
2026
toAug 01
2026
-
Jul 28 2026
Registration deadline
-
Jul 30 2026
Draft paper submission deadline
Sponsored By
The United Societies of Science
Organized By
Kongunadu College of Engineering and Technology
Supported By
IEEE Section
IEEE Madras Section
IEEE Madras Section
Contact Information
Previous Conferences
-
2026-07-30 India Trichy
2026 International Conference on Networks Computers and Communications
Submit Comment