A New Individual-decision Cognitive Learning Factor Selection Strategy

摘要

As an important parameter, up to day, many strategies for cognitive coefficient have been proposed However, there is still some work need to do. Since each particle maintains different living experience, e.g. feeding, nursing baby and so on. Thus different individual will make a different decision. However, this decision mechanism is not included in the improved particle swarm optimization (PSO). Therefore, with the assistant of mature individual decision way and mechanism, this paper dynamically adjusts cognitive coefficient by the change ratio of historical fitness value. Using several test functions to simulation, Simulation results show that its performance is superior to other two variants.