Based on BP Neural Network Classification of Medical History of Traditional Chinese Medicine Literature Research

• Published in: 2017 International Conference on Robots & Intelligent System (ICRIS) pp. 62 - 66
• Main Author: Hongmei Bao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2017
• Subjects: Intelligent systems; Manganese; Medical history literature category; Participles characteristic; Robots; The BP neural network; The simulation analysis
• DOI: 10.1109/ICRIS.2017.23

Chinese traditional medical history literature contains the Chinese medicine, Chinese medicine document, doctrine of traditional Chinese medicine and ancient medical Chinese courses, and subject classification and the cultivation of professional talents cannot leave based on the literature materials. As a result, the category of the medical history of literature of traditional Chinese medicine for precise classification subject construction is the important factor. In this paper, some 660 species of Medical Medical history of Medical university library literature study, extracting the characteristics of word segmentation, build the sample set input index, the literature established categories (1 - skilled doctor, 2 - Medical books, 3 - Schools, 4 - Other) as the output, using the BP neural network algorithm to study the relationship between input and output tag. The simulation results show that the BP neural network algorithm is effective, fast, convenient and accurate prediction of the category, the medical history literature to verify the effectiveness of the algorithm.