Animal Archives Management Based on Improved Krill Swarm Optimization Algorithm

  • Jing Liao
Keywords: Krill Swarm Optimization Algorithm, Improved Algorithm, Animal File Management

Abstract

Animal archives management is quite different from traditional paper archives, animal archives
management can record animal sounds and images more intuitively. At the same time, animal archives
management is composed of photosensitive materials and magnetic materials, there are higher requirements for
the preservation condition. Therefore, how to effectively manage the vast amount of animal archives
management information, it has always been a difficult problem for animal archives management managers in
every unit and enterprise. Today, information technology is becoming more and more popular. Using animal
archives management system to manage animal archives management data within the unit and enterprise is a
means to solve the problem of managing massive animal archives management data. In this paper, a new swarm
intelligence optimization algorithm, krill swarm algorithm is studied. An improved krill swarm optimization
algorithm is proposed to overcome the shortcomings of slow convergence speed and easy to fall into local
optimum. The optimization algorithm used in animal archives management combines the foraging behavior of
the watcher bee in the artificial bee colony algorithm, and makes use of the fast convergence and high precision
of the artificial bee colony algorithm. Combining the foraging behavior and self-diffusion behavior of krill
swarm in krill swarm algorithm, after several iterations, the performance of the algorithm is improved
effectively. On the basis of establishing good animal archives management, the improved krill swarm
optimization algorithm is used to search for animal file management. After optimization, the corresponding
animal file management under the corresponding load has been improved, which proves that the optimization
algorithm is feasible and effective. It can improve the application of animal archives management.

Published
2019-09-01