S. P. Sellapaandi
Papers
1
Total Citations
33
H-Index
1
About
S. P. Sellapaandi is a researcher at the forefront of applied artificial intelligence and computational ergonomics, with a primary focus on intelligent systems for retail and human-machine interaction. His most cited work, "A Novel Method for Exploring the Store Sales Forecasting using Fuzzy Pruning LS-SVM Approach" (2023, 33 citations), introduces an innovative hybrid machine learning technique that combines fuzzy logic with least-squares support vector machines to enhance sales prediction accuracy in convenience stores. This contribution addresses the growing complexity of modern retail environments, where intelligent robots, mobile systems, and automated stores demand robust forecasting methods. Sellapaandi’s research bridges the gap between theoretical AI models and practical ergonomic applications, demonstrating how computer-aided ergonomics can optimize both operational efficiency and user experience. His work has been instrumental in helping convenience stores adapt to a competitive landscape by leveraging data-driven insights for inventory and service optimization. With a growing citation impact, Sellapaandi continues to advance the integration of intelligent systems into everyday retail and ergonomic contexts, making his research highly relevant for students and practitioners exploring the intersection of machine learning, human factors, and smart commerce.
Research Focus
Key Achievements
Top Papers
- 1