Grey Wolf Optimization Algorithm Final Year Projects with Source Code
Grey Wolf Optimization Algorithm Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Grey Wolf Optimization Algorithm 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.
Grey Wolf Optimization Algorithm Final Year Projects
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A Distracted Driving Detection Model Based On Driving Performance
This project studies how a driver behaves when fully focused and when mentally distracted. Researchers collected driving data from many people using a simulator. They trained a deep learning model to recognize whether a driver is distracted just from the way they drive. The model works very well and can help detect unsafe driving in real time. -
Quantum Artificial Hummingbird Algorithm for Feature Selection of Social IoT
This project creates a smart method to pick only the most useful information from large Internet of Things data. It uses an improved search technique inspired by hummingbird behavior and quantum ideas. The method helps computers work faster and make better decisions with fewer inputs. Tests on many datasets show that it improves accuracy while reducing unnecessary data. -
A Fresh Look at Routing Protocols in Unmanned Aerial Vehicular Networks A Survey
This project studies how drones communicate with each other while moving in the air. It explains why choosing the best path for sending data is difficult because drone networks change quickly. The work compares different new routing methods and shows how well they perform. It also highlights remaining challenges and areas for future research in drone communication.
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Grey Wolf Optimization Algorithm Project Synopsis & Presentation
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