A novel firefly algorithm for parameter estimation
Gan Yu · International Journal of Wireless and Mobile Computing · 2019
Firefly algorithm (FA) is a recently proposed optimisation technique, which has shown good optimisation performance. However, FA suffers from slow convergence and low accuracy of solutions. To improve this case, this paper presents a novel FA (NFA) by combining two strategies. First, a local search operator is constructed for better fireflies in the population. Second, a concept of opposition-based learning is used for improving the accuracy of the global best solution. The experiment consists of two parts: (1) seven classical benchmark functions are used to verify the optimisation ability of NFA; and (2) NFA is used for parameter estimation of frequency modulated (FM) sound synthesis. Simulation results show the NFA approach can achieve promising performance.