Congratulations Nyantakyi Agyepong Emmanuel

Nyantakyi Agyepong Emmanuel is a graduating MPhil student from the Electrical & Electronic Engineering Department at KNUST.

His research interests are Fault Detection, Fault Classification, Fault Location, Algorithm Optimization, Process Simulation and Machine Learning.

For his MPhil project, he conducted a comprehensive fault detection, classification and location in transmission lines using a modified social spider optimisation feedforward neural network. He focused on modifying the social spider optimisation algorithm by applying fitness proportionate theory to select the optimal weight of the social spider optimisation algorithm to offer a better convergence rate and global optimum solution, which is implemented in the fault identification model to detect, classify and locate fault in transmission lines. 

He found that the improved social spider optimisation algorithm has significantly improved the fault identification model for detection, classification and location in terms of its performance matrices such as mean square error, regression and accuracy. 

KEEP has been instrumental in his academic success by providing financial support and internship opportunities. He is very grateful for the mentorship, encouragement and training he received from the staff and management of KEEP.

As he enters a new season of life, he plans to pursue a PhD in Power System Engineering. He hopes to continue advancing knowledge and innovation in his field.