Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

Table 2

Predictive performance comparison of soft-sensor models.

Predictive object	Predictive method	MSE	RMSE	NRMSE	SSE	MAPE
Concentrate grade; (%)	FNN	0.2416	0.4915	0.0223	12.081	0.5564
	PSO-FNN	0.1528	0.3909	0.0008	7.6402	0.4471
	GSA-FNN	0.0764	0.2764	0.0006	3.8209	0.2649
	PSOGSA-FNN	0.0300	0.1733	0.0004	1.5009	0.1890
Flotation recovery rate (%)	FNN	0.1751	0.4184	0.0163	8.7535	0.3089
	PSO-FNN	0.0627	0.2505	0.0004	3.1372	0.1751
	GSA-FNN	0.0447	0.2114	0.0003	2.2341	0.1422
	PSOGSA-FNN	0.0194	0.1393	0.0002	0.9707	0.1054