Oryctolagus Cuniculus Algorithm and Its Application in the Inversion Method of Asteroid Spectra Reflectance Template

Abstract

To improve the global optimization ability and convergence speed of the swarm intelligence algorithm, we proposed a new swarm intelligence optimization algorithm, namely the Oryctolagus cuniculus algorithm. This includes five mechanisms: the determination of safety zones, the cave escape, the agglomeration of Oryctolagus cuniculi, the maintenance of the Oryctolagus cuniculus king, and the zone competition. Each solution is represented by each Oryctolagus cuniculus’s position (including zone number and specific location number). The grass density and safety index at the location of the Oryctolagus cuniculus represents its fitness value. The determination of safety zones implies that predators such as eagles hunt Oryctolagus cuniculi in dangerous zones, and the zone without predators is considered a safety zone. The cave escape refers to the act of Oryctolagus cuniculi using a connected cave system to flee from a dangerous zone and reach a secure zone, thereby evading potential predators. We select the Oryctolagus cuniculus with higher fitness values as the king of each zone, and the Oryctolagus cuniculi gather towards the Oryctolagus cuniculus king. This mechanism ensures that Oryctolagus cuniculus mainly searches in zones with abundant grass and quickly finds the optimal solution. In the maintenance of the Oryctolagus cuniculus king, we choose the one with higher fitness values as the Oryctolagus cuniculus king. Zone competition is induced by an increase in the number of Oryctolagus cuniculi in zones with abundant grass by ordering the fitness values of each zone, and vice versa. We apply the Oryctolagus cuniculus algorithm to the inversion method of the asteroid spectra reflectance template. The experimental results show that compared with artificial rabbit optimization, this algorithm has a faster rate of convergence and better solution, effectively screens the reflectance template, and improves the Doppler difference velocimetry accuracy. In addition, the application of the Oryctolagus cuniculus algorithm to the knapsack problem also performs effectively.