ISSN: 0973-7510

E-ISSN: 2581-690X

Ping Zhang1, Guodong Gao2 , Cuiming Li3 and Xiangquan Gui4
1College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China.
2University hospital of Gansu traditional Chinese medicine, Lanzhou, China.
3College of Mechano-electronic Engineering, Lanzhou University of Technology, Lanzhou, China.
4College of Computer and Communication, Lanzhou University of Technology, Lanzhou, China.
J Pure Appl Microbiol. 2013;7(Spl. Edn.: April):241-248
© The Author(s). 2013
Received: 03/03/2013 | Accepted: 14/04/2013 | Published: 30/04/2013
Abstract

The combination of medicine and information science to analyze of clinical problems has become one of the hot subject to interdisciplinary study. This paper describes the analysis and design of digital treatment to the traditional Chinese drug fumigation (TCDF) to Lumbar disc herniation. The emphasis of this research is on the novel learning algorithm which is combined Yinger learning algorithm with dynamic fuzzy neural network of traditional Chinese drug fumigation fume to Lumbar disc herniation. The date preprocessing handle of date pretreatment and create a new local space by K-Vector Nearest Neighbors to remove extraneous matter from learning set. This method automatically adjusts fuzzy rules and networks weights based on local space to fit sampling data.  The simulation results show that the identification model can reveals pathological mechanism of Lumbar disc herniation and the result is feasible. The temperature regulating controller can response to changes in interference source with minimal energy loss to different types of patients. Compared with other methods, the new controller has better dynamics performance and anti-interference capability.

Keywords

Lumbar disc herniation, Yinger Learning Algorithm, Dynamic Fuzzy Neural Network, Nonlinear System, traditional Chinese drug fumigation

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