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
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;
Conference_Titel :
E-Health Networking, Digital Ecosystems and Technologies (EDT), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-5514-0
DOI :
10.1109/EDT.2010.5496600