Meejoung Kim
Theoretical bounds of generalization error for generalized extreme learning machine and random vector functional link network
Neural networks : the official journal of the International Neural Network Society
paper new bioinspired metaheuristic algorithm called lyrebird optimization algorithm loa imitates natural behavior lyrebirds wild introduced fundamental inspiration loa strategy lyrebirds faced danger situation lyrebirds scan surroundings carefully either run away hide somewhere immobile loa theory described mathematically modeled two phases exploration based simulation lyrebird escape strategy ii exploitation based simulation hiding strategy performance loa evaluated optimization cec 2017 test suite problem dimensions equal 10 30 50 100 optimization results show proposed loa approach high ability terms exploration exploitation balancing search process problemsolving space order evaluate capability loa dealing optimization tasks results obtained proposed approach compared performance twelve wellknown metaheuristic algorithms simulation results show loa superior performance compared competitor algorithms providing better results optimization benchmark functions achieving rank first best optimizer statistical analysis performance metaheuristic algorithms shows loa significant statistical superiority comparison compared algorithms addition efficiency loa handling realworld applications investigated dealing twentytwo constrained optimization problems cec 2011 test suite four engineering design problems simulation results show loa effective performance handling optimization tasks realworld applications providing better results compared competitor algorithms