The proposed methodology involves:

Simulated System Model : The UAV-RIS-assisted communication system is modeled with UAVs, ground users, and RIS elements.
Mathematical Modeling :  SINR, EMI, and energy efficiency are calculated based on predefined equations.
Deep Reinforcement Learning (DRL): The algorithm is trained in a simulated environment to optimize UAV deployment and RIS phase shifts dynamically.
Performance Evaluation :Various scenarios with different EMI levels are simulated, and results are compared with baseline models.

The results are synthetically generated through computational simulations rather than real-world dataset collection.