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Talk: Nature-Inspired Optimization Algorithms for Machine Learning: PSO and ABC

20/11/2019 de 11:00 a 13:00
Campus Nord (C3-005); Building C3; Room: 005
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This talk will touch on the overview of Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithm. The general structure and flowchart of both PSO and ABC will be introduced and benchmark test functions will be used to display the performance of PSO and ABC in obtaining the global minima for mathematical functions. This session will be carried using Matlab and the programming codes used will be explained step by step.


The talk will be performed by Dr. Kanendra Naidu:

who is a Senior Lecturer and the Head of Electrical Technology Section Universiti Kuala Lumpur, British Malaysian Institute (UniKL BMI). He has more than ten years of field and teaching experience. He has strong technical skills in the field of power system and artificial intelligence.

His postdoctoral tenure was with University Malaya Power and Energy System (UMPES), University of Malaya in which he conducted research on intentional islanding for generation and distribution system. Prior to this, he completed his doctorate degree (PhD) in the field of Electrical Engineering, University of Malaya in 2015. His PhD research area was focused upon discrete optimization for intentional islanding for generation system. He obtained his Master’s degree (M. Eng in Electrical Energy and Power System) from University of Malaya in 2011 and his Bachelor’s degree (B. Eng (Hons) Electrical and Electronic) from UCSI University in 2008.

His area of research is on Artificial Intelligence, Power System Control and Stability, Renewable Energy Integration and Intentional Islanding. He is actively involved in providing consultation for researchers from various universities on topics related to power system and engineering. Dr Kanendra has also authored journal papers and conference papers on swarm and evolutionary optimization for load frequency control, neural network application and energy management system.


Email: kanendra@unikl.edu.my / vkanendra@gmail.com