The Application of Multiobjective Genetic Algorithm to the Parameter Optimization of Single-Well Potential Stochastic Resonance Algorithm Aimed at Simultaneous Determination of Multiple Weak Chromatographic Peaks

Table 1

Calibration curves of Sudan dyes obtained via SSRA.

	a	b	c	d	e	f	g	Linear regression curve
Para Red
Conc.^1	14.4	21.6	28.8	36	43.2	57.6	72	𝐴=(156.1±6.999)𝑐+(1231±303.6); 𝑟=0.9950, SD = 348.1
𝐴^2	2916.6	4691.8	6107.6	7119.1	8108.6	10087.2	12301.7
Sudan I
Conc.	20.4	30.6	40.8	51	61.2	81.6	102	𝐴=(125.5±3.575)𝑐+(1599±219.6); 𝑟=0.9980, SD = 251.9
𝐴	4340.9	5189.6	7012.2	7959.4	8931.8	11877.7	14510
Sudan II
Conc.	50.2	75.3	100.4	125.5	150.6	200.8	251	𝐴=(96.20±2.178)𝑐+(3150±329.2); 𝑟=0.9987, SD = 377.6
𝐴	8201	10266	12857	14852.2	18052.2	21973.5	27599.5
Sudan III
Conc.	49.4	74.1	98.8	123.5	148.2	197.6	247	𝐴=(161.1±5.481)𝑐−(307.1±815.5); 𝑟=0.9971, SD = 935.2
𝐴	7171.1	11539.4	16825.9	18473.6	24582.9	30915.7	39575.2
Sudan IV
Conc.	121.2	181.8	242.4	303	363.6	484.8	606	𝐴=(61.77±2.273)𝑐+(1171±829.8); 𝑟=0.9966, SD = 951.6
𝐴	7367.9	12883.9	16985.5	20513.8	23914.1	29937.4	38845.5

1Conc.: concentration; ²𝐴: peak area obtained via SSRA.