[Retracted] Optimization and Evaluation of an Intelligent Short-Term Blood Glucose Prediction Model Based on Noninvasive Monitoring and Deep Learning Techniques

Figure 11

Clarke grid errors of the optimized deep learning models with CEEMDAN in 15 min prediction. (a) IBFO-GRU: area A: 98.4% and B: 1.6%. (b) IBFO-LSTM: area A: 94.3% and B: 5.7%. (c) IBFO-RNN: area A: 91.8% and B: 8.2%. (d) IBFO-GRU: area A: 92.7% and B: 7.3%. (e) IBFO-LSTM: area A: 91.3% and B: 8.7%. (f) IBFO-RNN: area A: 90.1% and B: 9.9%. (g) IBFO-GRU: area A: 92.5% and B: 7.5%. (h) IBFO-LSTM: area A: 91.8% and B: 8.2%. (i) IBFO-RNN: area A: 90.3% and B: 9.7%.

(a)

(b)

(c)

(d)

(e)

(f)

(g)

(h)

(i)