Multiple Linear Regression Model Based on Neural Network and Its Application in the MBR Simulation : Table 1

Table 1: Data table of the collected fluxes, pressure, and so forth.


Time	Temperature	Pressure	MLSS of inflow	MLSS of outflow	Total resistance	Fluxes
(h)	(C)	(MPa)	(mg/L)	(mg/L)	()	()

1	24	0.016	343.38	70.48	0.185	46.4
2	24	0.0168	378.15	83.87	0.2403	45.5
3	24	0.0175	392.42	87.06	0.2989	45.3
4	24	0.0243	472.43	85.63	0.3796	42.2
5	24	0.0268	483.73	59.62	0.3957	45.1
6	24	0.0291	583.16	95.05	0.441	42.2
7	24	0.0325	556.43	85.46	0.5119	39.7
8	24	0.0362	503.56	71.91	0.6075	37.3
9	24	0.0351	591.41	105.46	0.7143	31.4
10	24	0.0385	561.85	107.63	0.8421	28.9
11	24	0.0269	612.42	107.95	0.7623	21.7
12	24	0.0226	655.47	81.61	0.9737	14.5
13	24	0.0198	712.43	103.98	1.1659	11.2
14	24	0.0193	615.12	91.01	1.2911	10.5
15	24	0.0187	715.89	95.52	1.254	9.4