AN Identification and Prediction Model Based on PSO

被引：0
|
作者：
Wang, Hui [1 ]
Cai, Tie [1 ]
Cheng, Dongsheng [1 ]
Li, Kangshun [2 ]
Zhou, Ying [1 ]
机构：
[1] Shenzhen Inst Informat Technol, Shenzhen, Peoples R China
[2] Dongguan City Univ, Dongguan, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE | 2024年 / 18卷 / 01期
关键词：
Identification of Medicinal Material Types and Origins; K-Means; Slicing Clustering; Support Vector Machine;
D O I：
10.4018/IJCINI.344023
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
According to the spectral characteristics of different Chinese medicinal materials, the types of Chinese medicinal materials and the origin of Chinese medicinal materials are identified. Construct a fragmented clustering model. Firstly, the mid-infrared sample data is preprocessed, the Laida criterion model is established, and the abnormal data is eliminated; then the slicing model is used to divide the spectral wave into different regions according to the spectral characteristics. The data of each slice is clustered through the k-means clustering model. The origin of Chinese medicinal materials is identified by the support vector machine model. The data of Chinese medicinal materials with a known origin of a certain type of Chinese medicinal materials is used as the training sample set, and the data of Chinese medicinal materials with unknown origin is used as the test set.
引用
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页码：1 / 15
页数：266
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