DocumentCode
2818212
Title
Study on the causes of hypertension with improved BP neural network
Author
Dong, Xiuying ; Ping, Wang
Author_Institution
Electr. & Inf. Coll., Xihua Univ., Chengdu, China
Volume
1
fYear
2010
fDate
17-18 April 2010
Firstpage
21
Lastpage
24
Abstract
An improved neural network based on L-M (Levenberg-Marquard) algorithm neural network has been applied to the model for the analysis of factors on Hypertension. It can remedy the shortcoming of the slow convergence rate of traditional BP algorithm neural network. This model can determine which factors are the main reasons for high blood pressure. We have adopted the lattice fuzzy close-degree assessment and expert scoring method which quantified the various data of the factors on high blood pressure. We used the matlab to program and simulate. The results showed that: the improved BP neural network, can determine the main factors which causing the high blood pressure correctly, the error between the Predictive value and the actual value is very small. it reached the desired goal.
Keywords
backpropagation; health care; medical computing; neural nets; BP neural network; L-M algorithm; expert scoring method; high blood pressure; hypertension; lattice fuzzy close degree assessment; predictive value; Algorithm design and analysis; Blood pressure; Convergence; Ecosystems; Educational institutions; Hypertension; Information analysis; Mathematical model; Neural networks; Neurons; BP neural network; Close-degree grid; Hypertension; L-M algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
E-Health Networking, Digital Ecosystems and Technologies (EDT), 2010 International Conference on
Conference_Location
Shenzhen
Print_ISBN
978-1-4244-5514-0
Type
conf
DOI
10.1109/EDT.2010.5496600
Filename
5496600
Link To Document