Markov Decision Process Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Markov Decision Process projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

Markov Decision Process Final Year Projects

Deep Reinforcement Learning-Based Task Offloading and Resource Allocation for Industrial IoT in MEC Federation System

This study focuses on improving smart industrial systems that use IoT devices. These devices have limited power and memory, so the project uses mobile edge computing to help them process data more efficiently. The researchers developed a smart method using deep learning to decide how tasks are shared and resources are used across devices. Their approach reduces energy use and processing delays in real-world scenarios.
A DRL-Based Automated Algorithm Selection Framework for Cross-Layer QoS-Aware Scheduling and Antenna Allocation in Massive MIMO Systems

This project improves how mobile networks manage many antennas and users at the same time. It uses a learning model that picks the best scheduling and antenna methods based on current network traffic. The system learns from experience and adjusts its choices to keep users satisfied. Tests show it serves more users compared to fixed or traditional methods.

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At Final Year Projects, we provide complete guidance for Markov Decision Process IEEE projects for BE, BTech, ME, MSc, MCA and MTech students. We assist at every step from topic selection to coding, report writing, and result analysis.

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Markov Decision Process Project Synopsis & Presentation

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Markov Decision Process Final Year Projects with Source Code