Genetic algorithm-based interval type-2 fuzzy model identification for people with type-1 diabetes
Tsung-Chih Lin, Yi-Jie Huang, Josephine I-Ju Lin, Valentina Emilia Bălaş, Seshadhri Srinivasan · 2017
In this paper, the glucose regulation system is identified by interval type-2 fuzzy neural network (IT2FNN) based on genetic algorithm (GA) used to adapt the model parameters. The IT2FNN is constructed to identify the glucose regulation system of the people with diabetes type-1. The centers and widths of the memberships and output weights of the IT2FNN can be tuned by optimizing GA. The simulation result shows that the glucose-insulin behavior can be well identified by the advocated identification scheme.