Terahertz-Spectral Identification of Organic Compounds Based on Differential PCA-SVM Method

Substance	One-dimensional	Two-dimensional	Three-dimensional	Four-dimensional
TATP	-13.60	4.52	4.54	4.54
Black powder	-14.50	4.83	4.83	4.83
UN	-15.59	5.19	5.20	5.20
AN	-15.94	5.29	5.33	5.33
Dehydrated oxalic acid	-13.09	4.34	4.38	4.37
Dihydrated oxalic acid	-13.82	4.59	4.62	4.62
Stearic acid	-10.77	3.58	3.60	3.60
Sodium Stearate	-11.47	3.81	3.83	3.83
Citric acid monohydrate	-13.28	4.4	4.44	4.44
Citric acid dehydration	-15.59	5.17	5.21	5.21
Dihydrated sodium citrate	-10.94	3.64	3.65	3.65
Dehydrated sodium citrate	-14.81	4.93	4.94	4.94
Sodium citrate	-10.26	3.40	3.43	3.43
Uracil	-11.68	3.88	3.91	3.90
Sorbic acid	-14.38	4.76	4.81	4.81

Table 2. Parameters obtained from training in SVM
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Table 2. Parameters obtained from training in SVM
Method Differential PCA LDA F&A
Penalty factor 8 32 16
Parameter γ 4.88×10^-4 16 16

Table 3. Model identification results of 15 kinds of samples in test dataset
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Table 3. Model identification results of 15 kinds of samples in test dataset
Number oftest samples Featureextractionmethod Number ofidentifiedsamples Accuracyrate /%
15 Differential PCA 15 100
15 LDA 13 86.67
15 F &A 9 60

Table 4. Recognition performance of radial basis neural network
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Table 4. Recognition performance of radial basis neural network
Sampletest set Numberof testsamples Number ofidentifiedsamples Accuracyrate /%
Substance indatabase 15 14 93.33
Substance outof database 5 4 80.00

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Junxiu Liu, Bin Du, Yuqiang Deng, Jianwen Zhang, Haijiang Zhu. Terahertz-Spectral Identification of Organic Compounds Based on Differential PCA-SVM Method[J]. Chinese Journal of Lasers, 2019, 46(6): 0614039

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