An Improved Simulating-Fishing Optimization And Implication

Swarm intelligence algorithm as a new intelligent optimization technology was extensive concerned with its high precision and good robustness by computer science scholar. So far, people have proposed many kinds of optimization algorithm, such as artificial fish algorithm, genetic algorithm, glowworm swarm optimization algorithm, etc. It has been found that swarm intelligence algorithm is a kind of technology that can solve the global optimization problem effectively. The main contents and conclusions are as follows:(1) The first chapter introduces the background and purpose of intelligent algorithms, and then describes the research status of swarm intelligence and its wide application, given the structure and framework finely.(2) The second chapter introduces the swarm fishermen optimization algorithm (FSOA).(3) Chapter three was proposed an improving method that a simulation of the dynamic step strategy fisherman detection algorithm based on FSOA susceptible to duplication detection phenomenon, Fisherman by its current search direction was limited by the forward direction. Experiments show that this method can solve the disadvantage of slow convergence effectively.(4) Chapter four was proposed a new method that region search instead of Random detection strategy. Fishermen can use different search strategy according to them different environment, so as to make the precision got improved significantly.(5) Chapter five was proposed a new method that shrinkage method combined with particle swarm algorithm. It is required that the first find some local extremism, particle use different updating strategy according to their different environment in speed update. The experimental data show that this method can solve the most optimization problems effectively.