Gaussian Process Machine Learning Based ITO Algorithm

Taking the Gaussian process (GP) regression model as ITO´s fluctuation operator, we propose a new mixed algorithm called GITO in order to overcome the local minima problem. Through learning the particles´ mobility models, ITO´s capacity of local searching and global searching is strengthened. Meanwhile, we give the proof procedure to verify ITO´s fluctuation operator and GP are logically equivalent. Finally, the experiments show GITO´s better convergence rate and performance.