Development and Optimization for a New Planar Spring Using Finite Element Method, Deep Feedforward Neural Networks, and Water Cycle Algorithm

Table 5

DFNN parameters with 3 levels.

Variable	Level 1	Level 2	Level 3
Training function	Trainlm	Traincgb	Trainscg
Number of hidden layers	2	3	4
Number of nodes	7	9	11
Divide data	60 : 20 : 20	70 : 15 : 15	80 : 10 : 10