Table 3.

Configuration of the forecasting models for wellness conditions

Models		Optimized superior parameters
Deep learning-based	LSTM	h: 256, i: 100, η0: 0.6, f: 0.1. Optimized scheme of η: η·f when ε not improving every 10 epochs.
	BiLSTM	h: 256, i: 100, η0: 0.6, f: 0.1. Optimized scheme of η: η·f when ε not improving every 10 epochs.
Machine learning-based	ANN	h: 100, η0: 0.01, f: 0.01. Optimized scheme of η: η·f per 100 epochs
	SVM	C: 10, Γ: 0.01, Kernel: RBF Tolerance for stopping criterion: 10−3